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FastMath.abs
method wrapped as a ComposableFunction
.
BigFraction
.
boolean
elements; abstract.boolean
elements; abstract.byte
elements; abstract.byte
elements;
abstract.char
elements; abstract.char
elements;
abstract.int
, float
, etc.double
elements; abstract.double
elements;
abstract.FieldMatrix
methods regardless of the underlying storage.float
elements; abstract.float
elements;
abstract.FractionFormat
and BigFractionFormat
.int
elements; abstract.int
elements;
abstract.int
, float
, etc.long
elements; abstract.long
elements;
abstract.int
, float
, etc.int
, float
, etc.int
, float
, etc.int
, double
, etc.int
, double
, etc.int
, double
, etc.int
, double
, etc.int
, double
, etc.int
, double
, etc.RandomGenerator
interface.RealVector
interface.short
elements; abstract.short
elements;
abstract.StorelessUnivariateStatistic
interface.UnivariateStatistic
interface.StatProbe
,
for collecting statistics on a
variable that evolves in simulation time, with a piecewise-constant trajectory.FastMath.abs
method wrapped as a ComposableFunction
.
activeTests
, formatActiveTests
, etc.
tests
, then computes the p-values of those
that currently belong to activeTests,
and return these quantities in sVal and pVal, respectively.
Adams-Bashforth
and
Adams-Moulton
integrators.BinaryFunction
.
BigInteger
,
returning the result in reduced form.
v
.
v
.
m
.
m
.
v
.
v
.
m
.
m
.
m
.
m
.
m
.
v
.
m
.
v
.
v
.
add
, but adds the new event ev
immediately after the event other in the list.
from
(inclusive) and to
(inclusive) to the receiver.
from
(inclusive) and to
(inclusive) to the receiver.
from
(inclusive) and to
(inclusive) to the receiver.
from
(inclusive) and to
(inclusive) to the receiver.
from
(inclusive) and to
(inclusive) to the receiver.
from
(inclusive) and to
(inclusive) to the receiver.
from
(inclusive) and to
(inclusive) to the receiver.
from
(inclusive) and to
(inclusive) to the receiver.
from
(inclusive) and to
(inclusive) to the receiver.
from
(inclusive) and to
(inclusive) to the receiver.
from
(inclusive) and to
(inclusive) to the receiver.
from
(inclusive) and to
(inclusive) to the receiver.
from
(inclusive) and to
(inclusive) to the receiver.
from
(inclusive) and to
(inclusive) to the receiver.
from
(inclusive) and to
(inclusive) to the receiver.
from
(inclusive) and to
(inclusive) to the receiver.
from
(inclusive) and to
(inclusive) to the receiver.
from
(inclusive) and to
(inclusive) to the receiver.
add
, but adds the new event ev
immediately before the event other in the list.
data
.
x
, y
) to list of observed points
with a weight of 1.0.
x
, y
) to list of observed points
with a weight of weight
.
addRandomShift
(0, dim, stream),
where dim is the dimension of the digital net.
Frequency.addValue(Comparable)
instead
SummaryStatistics
from several data sets or
data set partitions.DoubleMatrix2D
; concentrates most functionality of this package.ContinuousDistribution
for the
Anderson-Darling distribution (see).AndersonDarlingDist
for the
distribution (see).double[]
arrays.
double[]
arrays.
double[]
arrays.
double[]
arrays.
RandomStream
to
return antithetic variates.s
static method to append str to the buffer.
f
static method to append x to the buffer.
f
static method to append x to the buffer.
d
static method to append x to the buffer.
d
static method to append x to the buffer.
format
static method with the same four arguments to append x to the buffer.
FieldElement
[][] array to store entries.v
as the
data for the unique column of the v.length x 1
matrix
created.
v
as the
data for the unique column of the v.length x 1
matrix
created.
FieldVector
interface with a FieldElement
array.RealVector
interface with a double array.FastMath.asin
method wrapped as a ComposableFunction
.
FastMath.atan
method wrapped as a ComposableFunction
.
FastMath.atan2
method wrapped as a BinaryFunction
.
average
, and stores
the results into the array a.
RandomStream
.barF
(alpha, beta, 0, 1, d, x).
barF
(alpha, 1.0, d, x).
NormalDist.barF01
.
barF
(0, 1, x).
barF
(0.0, 1.0, x).
RandomStream
implementation via the
newInstance
method.otherFrom
(inclusive) and otherTo
(inclusive) before the specified position into the receiver.
otherFrom
(inclusive) and otherTo
(inclusive) before the specified position into the receiver.
otherFrom
(inclusive) and otherTo
(inclusive) before the specified position into the receiver.
otherFrom
(inclusive) and otherTo
(inclusive) before the specified position into the receiver.
otherFrom
(inclusive) and otherTo
(inclusive) before the specified position into the receiver.
otherFrom
(inclusive) and otherTo
(inclusive) before the specified position into the receiver.
otherFrom
(inclusive) and otherTo
(inclusive) before the specified position into the receiver.
otherFrom
(inclusive) and otherTo
(inclusive) before the specified position into the receiver.
otherFrom
(inclusive) and otherTo
(inclusive) before the specified position into the receiver.
otherFrom
(inclusive) and otherTo
(inclusive) before the specified
position into the receiver.
otherFrom
(inclusive) and otherTo
(inclusive) before the specified
position into the receiver.
otherFrom
(inclusive) and otherTo
(inclusive) before the specified
position into the receiver.
otherFrom
(inclusive) and otherTo
(inclusive) before the specified
position into the receiver.
otherFrom
(inclusive) and otherTo
(inclusive) before the specified
position into the receiver.
otherFrom
(inclusive) and otherTo
(inclusive) before the specified
position into the receiver.
otherFrom
(inclusive) and otherTo
(inclusive) before the specified
position into the receiver.
otherFrom
(inclusive) and otherTo
(inclusive) before the specified
position into the receiver.
otherFrom
(inclusive) and otherTo
(inclusive) before the specified
position into the receiver.
DiscreteDistributionInt
for the Bernoulli
distribution with parameter p, where
0 <= p <= 1.BernoulliDist
).ContinuousDistribution
for
the beta distribution with shape parameters
α > 0 and β > 0, over the interval (a, b), where a < b.BetaRejectionLoglogisticGen
(s, s, dist).
BetaStratifiedRejectionGen
(s, s, dist).
BetaDist
to the case of a symmetrical
beta distribution over the interval [0, 1],
with shape parameters
α = β.BigDecimal
.
BigDecimal
following the passed
rounding mode.
BigDecimal
following the passed scale
and rounding mode.
BigFraction
equivalent to the passed BigInteger, ie
"num / 1".
BigFraction
given the numerator and denominator as
BigInteger
.
BigFraction
equivalent to the passed int, ie
"num / 1".
BigFraction
given the numerator and denominator as simple
int.
BigFraction
equivalent to the passed long, ie "num / 1".
BigFraction
given the numerator and denominator as simple
long.
FieldMatrix
/BigFraction
matrix to a RealMatrix
.
FieldMatrix
with a BigReal
parameterArray2DRowFieldMatrix
with a BigReal
parameterd
as the underlying
data array.
d
as the underlying
data array.
d
as the underlying data array.
v
as the
data for the unique column of the v.length x 1
matrix
created.
BinaryChromosome
s.EventList
using a binary search tree.n choose k
", the number of
k
-element subsets that can be selected from an
n
-element set.
double
representation of the Binomial
Coefficient, "n choose k
", the number of
k
-element subsets that can be selected from an
n
-element set.
log
of the Binomial
Coefficient, "n choose k
", the number of
k
-element subsets that can be selected from an
n
-element set.
DiscreteDistributionInt
for the
binomial distribution with parameters n and p, where
n is a positive integer and
0 <= p <= 1.BinomialDistribution
.ContinuousDistribution2Dim
for the bivariate
normal distribution.BiNormalDist
for the bivariate
normal distribution
using a translation of Donnelly's FORTRAN code.BiNormalDonnellyDist
(rho, 15).
BiNormalDonnellyDist
(mu1, sigma1, mu2, sigma2, rho, 15).
BiNormalDist
for the bivariate
normal distribution
using Genz's algorithm as described in.BisectionSolver.solve(UnivariateRealFunction, double, double)
or
UnivariateRealSolver.solve(UnivariateRealFunction, double, double, double)
method.
ContinuousDistribution2Dim
for the standard bivariate Student's t distribution.boolean
elements; implemented with arrays.boolean
elements; implemented with
arrays.CategoryChart
. lowerBound <= a < initial < b <= upperBound
f(a) * f(b) < 0
If f is continuous on [a,b],
this means that a
and b
bracket a root of f.
lowerBound <= a < initial < b <= upperBound
f(a) * f(b) <= 0
If f is continuous on [a,b],
this means that a
and b
bracket a root of f.
100, 50
(see the
other constructor
).
BrentSolver.solve(UnivariateRealFunction, double, double)
or
UnivariateRealSolver.solve(UnivariateRealFunction, double, double, double)
method.
byte
elements; implemented with arrays.byte
elements; implemented with arrays.ContinuousDistribution
for
the Cauchy distribution
with location parameter α
and scale parameter β > 0.CauchyDistribution
.FastMath.cbrt
method wrapped as a ComposableFunction
.
cdf
(alpha, beta, 0, 1, d, x).
cdf
(alpha, alpha, d, x).
GumbelDist
.
cdf01
.
cdf
(0, 1, x).
cdf
(0.0, 1.0, x).
long >= value
.
long >= value
.
long >= value
.
FastMath.ceil
method wrapped as a ComposableFunction
.
cern.colt.matrix
, without subsetting or supersetting.DoubleMatrix2D
and DoubleMatrix1D
.DoubleMatrix2D
and DoubleMatrix1D
.FloatMatrix2D
and FloatMatrix1D
.char
elements; implemented with arrays.char
elements; implemented with arrays.checkOrder
method). To be removed in 3.0.
chi2
,
except that the expected
number of observations per category is assumed to be the same for
all categories, and equal to nbExp.
ContinuousDistribution
for the chi
distribution with shape parameter
v > 0, where the number of degrees of freedom
v is a positive integer.observed
and expected
frequency counts.
counts
array, viewed as a two-way table.
observed
and expected
frequency counts.
observed1
and observed2
.
ChiSquaredDistribution
ContinuousDistribution
for
the chi-square distribution with n degrees of freedom,
where n is a positive integer.ChiSquareDist
with
faster but less accurate methods.ContinuousDistribution
for
the noncentral chi-square distribution with ν degrees of freedom
and noncentrality parameter λ, where ν > 0 and
λ > 0.observed
frequency counts to those in the expected
array.
alpha
.
counts
array, viewed as a two-way table.
alpha
.
observed
frequency counts to those in the expected
array.
alpha
.
observed1
and
observed2
.
UnknownDistributionChiSquareTest
interface.Chromosome
objects.Chrono
class extends the
AbstractChrono
class and computes the CPU time for the current thread only.AbstractRandomGenerator.nextGaussian()
.
BitMatrix
produces a new BitMatrix
that is equal to it.
BitVector
produces a new BitVector
that is equal to it.
BitMatrix
produces a new BitMatrix
that is equal to it.
BitVector
produces a new BitVector
that is equal to it.
CloneableRandomStream
extends RandomStream
and Cloneable
.valuesFileURL
after use in REPLAY_MODE.
Clusterable
points.data
sorted by comparator
.
Complex
utilities functions.UnivariateRealFunction
that can be composed with other functions.KernelDensityGen.getBaseBandwidth
(dist) in package randvar.
valuesFileURL
, using the default number of bins.
valuesFileURL
and binCount
bins.
NonLinearConjugateGradientOptimizer
.connectToDatabase
(url.openStream()).
connectToDatabase
(new FileInputStream (file)).
connectToDatabase
(new FileInputStream (fileName)).
connectToDatabase
with the stream obtained from
the resource resource.
ConvergenceException.ConvergenceException(Localizable, Object...)
ConvergenceException.ConvergenceException(Throwable, Localizable, Object...)
IterativeAlgorithm
. The concept of "accuracy" is
currently is also contained in SimpleRealPointChecker
and similar classes.clone()
and casts the result.
clone()
and casts the result.
clone()
and casts the result.
clone()
and casts the result.
clone()
and casts the result.
clone()
and casts the result.
clone()
and casts the result.
clone()
and casts the result.
clone()
and casts the result.
clone()
and casts the result.
clone()
and casts the result.
clone()
and casts
the result.
clone()
and casts
the result.
clone()
and casts
the result.
clone()
and casts
the result.
clone()
and casts
the result.
clone()
and casts
the result.
clone()
and casts
the result.
clone()
and casts the
result.
clone()
and casts
the result.
clone()
and casts the result.
clone()
and casts the result.
clone()
and casts the result.
clone()
and casts the result.
clone()
and casts the result.
clone()
and casts
the result.
clone()
and casts
the result.
clone()
and casts
the result.
clone()
and casts
the result.
clone()
and casts
the result.
clone()
and casts
the result.
clone()
and casts
the result.
clone()
and casts
the result.
clone()
and casts
the result.
clone()
and casts
the result.
clone()
and casts
the result.
clone()
and casts
the result.
clone()
and casts
the result.
clone()
and casts
the result.
clone()
and
casts the result.
clone()
and casts
the result.
RandomVectorGenerator
that generates vectors with with
correlated components.covariance
for computing
the sample correlation matrix.
FastMath.cos
method wrapped as a ComposableFunction
.
FastMath.cosh
method wrapped as a ComposableFunction
.
ContinuousDistribution
for the
Cramér-von Mises distribution (see).Random
using the supplied
RandomGenerator
.
MathRuntimeException.createArithmeticException(Localizable, Object...)
ArithmeticException
with specified formatted detail message.
MathRuntimeException.createArrayIndexOutOfBoundsException(Localizable, Object...)
ArrayIndexOutOfBoundsException
with specified formatted detail message.
MatrixUtils.createFieldIdentityMatrix(Field, int)
MatrixUtils.createFieldMatrix(FieldElement[][])
MatrixUtils.createFieldMatrix(FieldElement[][])
MatrixUtils.createFieldMatrix(FieldElement[][])
MatrixUtils.createFieldMatrix(FieldElement[][])
MatrixUtils.createColumnFieldMatrix(FieldElement[])
MatrixUtils.createColumnFieldMatrix(FieldElement[])
MatrixUtils.createColumnFieldMatrix(FieldElement[])
FieldMatrix
using the data from the input
array.
RealMatrix
using the data from the input
array.
MathRuntimeException.createConcurrentModificationException(Localizable, Object...)
ConcurrentModificationException
with specified formatted detail message.
SummaryStatistics
whose data will be
aggregated with those of this AggregateSummaryStatistics
.
Event
object used for synchronization.
MathRuntimeException.createEOFException(Localizable, Object...)
EOFException
with specified formatted detail message.
dimension x dimension
identity matrix.
FieldMatrix
with specified dimensions.
FieldMatrix
whose entries are the the values in the
the input array.
FieldVector
using the data from the input array.
MathRuntimeException.createIllegalArgumentException(Localizable, Object...)
IllegalArgumentException
with specified formatted detail message.
IllegalArgumentException
with specified nested
Throwable
root cause.
MathRuntimeException.createIllegalStateException(Localizable, Object...)
IllegalStateException
with specified formatted detail message.
RuntimeException
for an internal error.
IOException
with specified nested
Throwable
root cause.
MathRuntimeException.createNoSuchElementException(Localizable, Object...)
NoSuchElementException
with specified formatted detail message.
MathRuntimeException.createNullPointerException(Localizable, Object...)
MathRuntimeException.createParseException(int, Localizable, Object...)
ParseException
with specified
formatted detail message.
dimension x dimension
identity matrix.
RealMatrix
with specified dimensions.
RealMatrix
whose entries are the the values in the
the input array.
RealVector
using the data from the input array.
MatrixUtils.createRowFieldMatrix(FieldElement[])
MatrixUtils.createRowFieldMatrix(FieldElement[])
MatrixUtils.createRowFieldMatrix(FieldElement[])
FieldMatrix
using the data from the input
array.
RealMatrix
using the data from the input
array.
MathUnsupportedOperationException
instead.
Tally
.
Tally
.
TallyStore
.
TallyStore
.
x
).
x
).
x
).
x
).
HistogramType
.FREQUENCY.
CycleBasedPointSet
, except that the successive
values in the cycles are stored as integers in the range
{0,..., 2k -1}, where
1 <= k <= 31.d
(0, 1, x).
d
(fieldwidth, 1, x).
sequence
of objects of type T according to the
permutation this chromosome represents.
sequence
of objects of type T according to the
permutation this chromosome represents.
Property.DEFAULT
attached for tolerance.
DoubleProperty.DEFAULT
attached for
tolerance.
DoubleProperty.DEFAULT
attached for
tolerance.
FloatProperty.DEFAULT
attached for
tolerance.
FloatProperty.DEFAULT
attached for
tolerance.
FieldMatrixChangingVisitor
interface.FieldMatrixPreservingVisitor
interface.RealMatrixChangingVisitor
interface.RealMatrixPreservingVisitor
interface.Sim
, and the no-argument constructor of Event
.
DenseDoubleLUDecomposition
, avoiding
unnecessary memory allocation and copying.DenseFloatLUDecomposition
, avoiding
unnecessary memory allocation and copying.density
(alpha, beta, 0, 1, x).
density
(0, 1, x).
RealMatrix
field in a class.
RealVector
field in a class.
Dfp
which hides the radix-10000 artifacts of the superclass.Dfp
.diff
(IntArrayList,IntArrayList,int,int,int,int),
but for the continuous case.
MultivariateRealFunction
representing a differentiable
multivariate real function.scalar differentiable objective
functions
.MultivariateVectorialFunction
representing a differentiable
multivariate vectorial function.vectorial differentiable objective functions
.UnivariateMatrixFunction
representing a differentiable univariate matrix function.UnivariateRealFunction
representing a differentiable univariate real function.UnivariateVectorialFunction
representing a differentiable univariate vectorial function.DigitalNet
for the base b = 2.DigitalNetBase2FromFile
(filename, r, 31, s1) where
s1 is the dimension and r is given in data file filename.
DigitalNetFromFile
(filename, r, r, s) where
s is the dimension and r is given in data file filename.
org.apache.commons.math.exception
.ContinuousDistributionMulti
for the
Dirichlet distribution with parameters
(α1,...,αd),
αi > 0.RandomMultivariateGen
for a
Dirichlet distribution.i initial elements of the array.
- discardMostRecentElements(int) -
Method in class org.apache.commons.math.util.ResizableDoubleArray
- Discards the
i last elements of the array.
- DiscreteDistIntChart - Class in umontreal.iro.lecuyer.charts
- This class provides tools to plot the mass function and the cumulative
probability of a discrete probability distribution over the integers.
- DiscreteDistIntChart(DiscreteDistributionInt) -
Constructor for class umontreal.iro.lecuyer.charts.DiscreteDistIntChart
- Constructor for a new DiscreteDistIntChart instance used to plot the
probabilities of the
discrete distribution dist over the integers.
- DiscreteDistIntChart(DiscreteDistributionInt, int, int) -
Constructor for class umontreal.iro.lecuyer.charts.DiscreteDistIntChart
- Constructor for a new DiscreteDistIntChart instance used to plot the
probabilities of the
discrete distribution dist over the interval [a, b].
- DiscreteDistribution - Class in jhplot.math.num.pdf
- Base discrete distribution.
- DiscreteDistribution() -
Constructor for class jhplot.math.num.pdf.DiscreteDistribution
-
- DiscreteDistribution - Interface in org.apache.commons.math.distribution
- Base interface for discrete distributions.
- DiscreteDistribution - Class in umontreal.iro.lecuyer.probdist
- Classes implementing discrete distributions over a
finite set of real numbers should inherit from this class.
- DiscreteDistribution(double[], double[], int) -
Constructor for class umontreal.iro.lecuyer.probdist.DiscreteDistribution
- Constructs a discrete distribution over the n values
contained in array obs, with probabilities given in array prob.
- DiscreteDistribution(double[]) -
Constructor for class umontreal.iro.lecuyer.probdist.DiscreteDistribution
- Constructs a discrete distribution whose parameters are given
in a single ordered array: params[0] contains n, the number of
values to consider.
- DiscreteDistributionInt - Class in umontreal.iro.lecuyer.probdist
- Classes implementing discrete distributions over the integers should
inherit from this class.
- DiscreteDistributionInt() -
Constructor for class umontreal.iro.lecuyer.probdist.DiscreteDistributionInt
-
- DiscreteDistributionIntMulti - Class in umontreal.iro.lecuyer.probdistmulti
- Classes implementing multi-dimensional discrete distributions over the integers
should inherit from this class.
- DiscreteDistributionIntMulti() -
Constructor for class umontreal.iro.lecuyer.probdistmulti.DiscreteDistributionIntMulti
-
- DiscreteRandomVariable - Interface in jhplot.math.num.random
- A random variable generator for a discrete distribution.
- disnan(double) -
Method in class org.netlib.lapack.LAPACK
-
..
- display() -
Method in class cern.colt.Timer
- Prints the elapsed time on System.out
- displayLimits() -
Method in class flanagan.interpolation.BiCubicSpline
-
- displayLimits() -
Method in class flanagan.interpolation.BiCubicSplineFirstDerivative
-
- displayLimits() -
Method in class flanagan.interpolation.BiCubicSplinePartialDerivative
-
- displayLimits() -
Method in class flanagan.interpolation.CubicSpline
-
- displayLimits() -
Method in class flanagan.interpolation.PolyCubicSpline
-
- displayLimits() -
Method in class flanagan.interpolation.QuadriCubicSpline
-
- displayLimits() -
Method in class flanagan.interpolation.TriCubicSpline
-
- disposeMe() -
Method in class jhplot.GHMargin
- Dispose this canvas
- distance(DoubleMatrix2D, Statistic.VectorVectorFunction) -
Static method in class cern.colt.matrix.doublealgo.Statistic
- Constructs and returns the distance matrix of the given matrix.
- distance(DoubleMatrix2D, DoubleStatistic.VectorVectorFunction) -
Static method in class cern.colt.matrix.tdouble.algo.DoubleStatistic
- Constructs and returns the distance matrix of the given matrix.
- distance(FloatMatrix2D, FloatStatistic.VectorVectorFunction) -
Static method in class cern.colt.matrix.tfloat.algo.FloatStatistic
- Constructs and returns the distance matrix of the given matrix.
- distance(SpacePoint, SpacePoint) -
Static method in class hephysics.vec.SpacePoint
- Return the distance between two space points.
- distance(DataPoint, DataPoint) -
Static method in class jminhep.cluster.DataPoint
- Returns the distance between two data points
- distance(Rotation, Rotation) -
Static method in class org.apache.commons.math.geometry.Rotation
- Compute the distance between two rotations.
- distance(Vector3D, Vector3D) -
Static method in class org.apache.commons.math.geometry.Vector3D
- Compute the distance between two vectors according to the L2 norm.
- distance(double[], double[]) -
Static method in class org.apache.commons.math.util.MathUtils
- Calculates the L2 (Euclidean) distance between two points.
- distance(int[], int[]) -
Static method in class org.apache.commons.math.util.MathUtils
- Calculates the L2 (Euclidean) distance between two points.
- distance1(Vector3D, Vector3D) -
Static method in class org.apache.commons.math.geometry.Vector3D
- Compute the distance between two vectors according to the L1 norm.
- distance1(double[], double[]) -
Static method in class org.apache.commons.math.util.MathUtils
- Calculates the L1 (sum of abs) distance between two points.
- distance1(int[], int[]) -
Static method in class org.apache.commons.math.util.MathUtils
- Calculates the L1 (sum of abs) distance between two points.
- distanceFrom(T) -
Method in interface org.apache.commons.math.stat.clustering.Clusterable
- Returns the distance from the given point.
- distanceFrom(EuclideanIntegerPoint) -
Method in class org.apache.commons.math.stat.clustering.EuclideanIntegerPoint
- Returns the distance from the given point.
- distanceInf(Vector3D, Vector3D) -
Static method in class org.apache.commons.math.geometry.Vector3D
- Compute the distance between two vectors according to the L∞ norm.
- distanceInf(double[], double[]) -
Static method in class org.apache.commons.math.util.MathUtils
- Calculates the L∞ (max of abs) distance between two points.
- distanceInf(int[], int[]) -
Static method in class org.apache.commons.math.util.MathUtils
- Calculates the L∞ (max of abs) distance between two points.
- distanceSq(Vector3D, Vector3D) -
Static method in class org.apache.commons.math.geometry.Vector3D
- Compute the square of the distance between two vectors.
- distanceSqrt(DataPoint, DataPoint) -
Static method in class jminhep.cluster.DataPoint
- Returns the squared distance between two data points
- DistinctNumberList - Class in cern.colt.list
- Resizable compressed list holding numbers; based on the fact that a number from a large list with few distinct values need not take more than log(distinctValues) bits; implemented with a MinMaxNumberList.
- DistinctNumberList(long[], int) -
Constructor for class cern.colt.list.DistinctNumberList
- Constructs an empty list with the specified initial capacity and the specified distinct values allowed to be hold in this list.
- DistinctNumberList - Class in cern.colt.list.tlong
- Resizable compressed list holding numbers; based on the fact that a number
from a large list with few distinct values need not take more than
log(distinctValues) bits; implemented with a
MinMaxNumberList.
- DistinctNumberList(long[], int) -
Constructor for class cern.colt.list.tlong.DistinctNumberList
- Constructs an empty list with the specified initial capacity and the
specified distinct values allowed to be hold in this list.
- Distribution - Interface in jhplot.math.num.pdf
- Base statistical distribution.
- Distribution - Interface in org.apache.commons.math.distribution
- Base interface for probability distributions.
- Distribution - Interface in umontreal.iro.lecuyer.probdist
- This interface should be implemented by all classes supporting
discrete and continuous distributions.
- DistributionFactory - Class in umontreal.iro.lecuyer.probdist
- This class implements a string API for the package probdist.
- Distributions - Class in cern.jet.random
- Contains methods for conveniently generating pseudo-random numbers from special distributions such as the Burr, Cauchy, Erlang, Geometric, Lambda, Laplace, Logistic, Weibull, etc.
- Distributions - Class in cern.jet.random.tdouble
- Contains methods for conveniently generating pseudo-random numbers from
special distributions such as the Burr, Cauchy, Erlang, Geometric, Lambda,
Laplace, Logistic, Weibull, etc.
- distroy() -
Method in class jhplot.HPlot
- Remove the canvas frame
- distroy() -
Method in class jhplot.HPlot2D
- Remove the canvas frame
- div(DoubleMatrix1D, double) -
Static method in class cern.colt.matrix.doublealgo.Transform
- Deprecated. A = A / s <=> A[i] = A[i] / s.
- div(DoubleMatrix1D, DoubleMatrix1D) -
Static method in class cern.colt.matrix.doublealgo.Transform
- Deprecated. A = A / B <=> A[i] = A[i] / B[i].
- div(DoubleMatrix2D, double) -
Static method in class cern.colt.matrix.doublealgo.Transform
- Deprecated. A = A / s <=> A[row,col] = A[row,col] / s.
- div(DoubleMatrix2D, DoubleMatrix2D) -
Static method in class cern.colt.matrix.doublealgo.Transform
- Deprecated. A = A / B <=> A[row,col] = A[row,col] / B[row,col].
- div -
Static variable in class cern.jet.math.Functions
- Function that returns a / b.
- div(double) -
Static method in class cern.jet.math.Functions
- Constructs a function that returns a / b.
- div -
Static variable in class cern.jet.math.IntFunctions
- Function that returns a / b.
- div(int) -
Static method in class cern.jet.math.IntFunctions
- Constructs a function that returns a / b.
- div(double) -
Static method in class cern.jet.math.Mult
- a / constant.
- div(double[], double, double) -
Static method in class cern.jet.math.tdcomplex.DComplex
-
- div(double[], double[]) -
Static method in class cern.jet.math.tdcomplex.DComplex
-
- div -
Static variable in class cern.jet.math.tdcomplex.DComplexFunctions
- Binary functions
- div(double[]) -
Static method in class cern.jet.math.tdcomplex.DComplexFunctions
-
- div(double) -
Static method in class cern.jet.math.tdcomplex.DComplexFunctions
-
- div(double[]) -
Static method in class cern.jet.math.tdcomplex.DComplexMult
- a / constant.
- div -
Static variable in class cern.jet.math.tdouble.DoubleFunctions
- Function that returns a / b.
- div(double) -
Static method in class cern.jet.math.tdouble.DoubleFunctions
- Constructs a function that returns a / b.
- div(double) -
Static method in class cern.jet.math.tdouble.DoubleMult
- a / constant.
- div(float[], float, float) -
Static method in class cern.jet.math.tfcomplex.FComplex
-
- div(float[], float[]) -
Static method in class cern.jet.math.tfcomplex.FComplex
-
- div -
Static variable in class cern.jet.math.tfcomplex.FComplexFunctions
- Binary functions
- div(float[]) -
Static method in class cern.jet.math.tfcomplex.FComplexFunctions
-
- div(float) -
Static method in class cern.jet.math.tfcomplex.FComplexFunctions
-
- div(float[]) -
Static method in class cern.jet.math.tfcomplex.FComplexMult
- a / constant.
- div -
Static variable in class cern.jet.math.tfloat.FloatFunctions
- Function that returns a / b.
- div(float) -
Static method in class cern.jet.math.tfloat.FloatFunctions
- Constructs a function that returns a / b.
- div(float) -
Static method in class cern.jet.math.tfloat.FloatMult
- a / constant.
- div -
Static variable in class cern.jet.math.tint.IntFunctions
- Function that returns a / b.
- div(int) -
Static method in class cern.jet.math.tint.IntFunctions
- Constructs a function that returns a / b.
- div(int) -
Static method in class cern.jet.math.tint.IntMult
- a / constant.
- div -
Static variable in class cern.jet.math.tlong.LongFunctions
- Function that returns a / b.
- div(long) -
Static method in class cern.jet.math.tlong.LongFunctions
- Constructs a function that returns a / b.
- div(long) -
Static method in class cern.jet.math.tlong.LongMult
- a / constant.
- div(Binner1D, Binner1D, Binner1D) -
Static method in class hep.aida.ref.histogram.binner.BinnerMath
-
- div(Complex) -
Method in class jhplot.math.Complex
- Division of Complex numbers (doesn't change this Complex number).
- div(float) -
Method in class jhplot.v3d.Vector3d
-
- divide(String, IDataPointSet, IDataPointSet) -
Method in class hep.aida.ref.histogram.DataPointSetFactory
-
- divide(String, IHistogram1D, IHistogram1D) -
Method in class hep.aida.ref.histogram.HistogramFactory
- Divides two 1D Histogram
- divide(String, IHistogram2D, IHistogram2D) -
Method in class hep.aida.ref.histogram.HistogramFactory
- Divides two 2D Histogram
- divide(String, IHistogram3D, IHistogram3D) -
Method in class hep.aida.ref.histogram.HistogramFactory
- Divides two 3D Histogram
- divide(double) -
Method in class jhplot.math.Complex
- Returns this complex divided by the specified factor.
- divide(double[], double[]) -
Static method in class jhplot.math.LinearAlgebra
- Element-wise ratio of two arrays.
- divide(double[], double) -
Static method in class jhplot.math.LinearAlgebra
- Divide each element of an array by a scalar.
- divide(double[][], double) -
Static method in class jhplot.math.LinearAlgebra
- Divide each element of a matrix by a scalar
- divide(double[][], double[]...) -
Static method in class jhplot.math.LinearAlgebra
-
- divide(ValueErr, double) -
Method in class jhplot.math.ValueErr
- Division of this ValueErr number by a ValueErr number.
- divide(ValueErr, ValueErr, double) -
Static method in class jhplot.math.ValueErr
- Division of two ValueErr numbers a/b with correlation
- divide(ValueErr) -
Method in class jhplot.math.ValueErr
- Division of this ValueErr number by a ValueErr number without correlation
- divide(ValueErr, ValueErr) -
Static method in class jhplot.math.ValueErr
- Division of two ValueErr numbers a/b without correlation
- divide(double) -
Method in class jhplot.math.ValueErr
- Division of this ValueErr number by a double
- divide(double, ValueErr) -
Static method in class jhplot.math.ValueErr
- Division of a double, a, by a ValueErr number, b
- divide(double, double) -
Static method in class jhplot.math.ValueErr
- Divide a double number by a double and return quotient as ValueErr
- DIVIDE -
Static variable in class org.apache.commons.math.analysis.BinaryFunction
- Deprecated. The / operator method wrapped as a
BinaryFunction
.
- divide(UnivariateRealFunction) -
Method in class org.apache.commons.math.analysis.ComposableFunction
- Return a function dividing the instance by another function.
- divide(Complex) -
Method in class org.apache.commons.math.complex.Complex
- Return the quotient of this complex number and the given complex number.
- divide(Dfp) -
Method in class org.apache.commons.math.dfp.Dfp
- Divide this by divisor.
- divide(int) -
Method in class org.apache.commons.math.dfp.Dfp
- Divide by a single digit less than radix.
- divide(T) -
Method in interface org.apache.commons.math.FieldElement
- Compute this ÷ a.
- divide(BigInteger) -
Method in class org.apache.commons.math.fraction.BigFraction
-
Divide the value of this fraction by the passed
BigInteger
,
ie "this * 1 / bg", returning the result in reduced form.
- divide(int) -
Method in class org.apache.commons.math.fraction.BigFraction
-
Divide the value of this fraction by the passed int, ie
"this * 1 / i", returning the result in reduced form.
- divide(long) -
Method in class org.apache.commons.math.fraction.BigFraction
-
Divide the value of this fraction by the passed long, ie
"this * 1 / l", returning the result in reduced form.
- divide(BigFraction) -
Method in class org.apache.commons.math.fraction.BigFraction
-
Divide the value of this fraction by another, returning the result in
reduced form.
- divide(Fraction) -
Method in class org.apache.commons.math.fraction.Fraction
- Divide the value of this fraction by another.
- divide(int) -
Method in class org.apache.commons.math.fraction.Fraction
- Divide the fraction by an integer.
- divide(BigReal) -
Method in class org.apache.commons.math.util.BigReal
- Compute this ÷ a.
- dividedBy(Matrix) -
Method in class jhplot.bsom.Matrix
- Matrix division: X\Y.
- dividedBy(Matrix, int) -
Method in class jhplot.bsom.Matrix
- Matrix division with bandwidth: X\Y.
- DividedDifferenceInterpolator - Class in org.apache.commons.math.analysis.interpolation
- Implements the
Divided Difference Algorithm for interpolation of real univariate
functions.
- DividedDifferenceInterpolator() -
Constructor for class org.apache.commons.math.analysis.interpolation.DividedDifferenceInterpolator
-
- divideEqual(ValueErr) -
Method in class jhplot.math.ValueErr
- Division of this ValueErr number by a ValueErr number and replace it by
the quotient without correlation
- divideEqual(ValueErr, double) -
Method in class jhplot.math.ValueErr
- Division of this ValueErr number by a ValueErr number and replace this by
the quotient
- divideEqual(double) -
Method in class jhplot.math.ValueErr
- Division of this ValueErr number by a double and replace this by the
quotient
- divideLU(double[][], double[]...) -
Static method in class jhplot.math.LinearAlgebra
-
- divideQR(double[][], double[]...) -
Static method in class jhplot.math.LinearAlgebra
-
- divNeg -
Static variable in class cern.jet.math.tdouble.DoubleFunctions
- Function that returns -(a / b).
- divNeg -
Static variable in class cern.jet.math.tfloat.FloatFunctions
- Function that returns -(a / b).
- divNeg -
Static variable in class cern.jet.math.tint.IntFunctions
- Function that returns -(a / b).
- divNeg -
Static variable in class cern.jet.math.tlong.LongFunctions
- Function that returns -(a / b).
- dlabad(doubleW, doubleW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dlabrd(int, int, int, double[], int, double[], double[], double[], double[], double[], int, double[], int) -
Method in class org.netlib.lapack.LAPACK
-
..
- dlacn2(int, double[], double[], int[], doubleW, intW, int[]) -
Method in class org.netlib.lapack.LAPACK
-
..
- dlacon(int, double[], double[], int[], doubleW, intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dlacpy(String, int, int, double[], int, double[], int) -
Method in class org.netlib.lapack.LAPACK
-
..
- dladiv(double, double, double, double, doubleW, doubleW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dlae2(double, double, double, doubleW, doubleW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dlaebz(int, int, int, int, int, int, double, double, double, double[], double[], double[], int[], double[], double[], intW, int[], double[], int[], intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dlaed0(int, int, int, double[], double[], double[], int, double[], int, double[], int[], intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dlaed1(int, double[], double[], int, int[], doubleW, int, double[], int[], intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dlaed2(intW, int, int, double[], double[], int, int[], doubleW, double[], double[], double[], double[], int[], int[], int[], int[], intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dlaed3(int, int, int, double[], double[], int, double, double[], double[], int[], int[], double[], double[], intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dlaed4(int, int, double[], double[], double[], double, doubleW, intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dlaed5(int, double[], double[], double[], double, doubleW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dlaed6(int, boolean, double, double[], double[], double, doubleW, intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dlaed7(int, int, int, int, int, int, double[], double[], int, int[], doubleW, int, double[], int[], int[], int[], int[], int[], double[], double[], int[], intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dlaed8(int, intW, int, int, double[], double[], int, int[], doubleW, int, double[], double[], double[], int, double[], int[], intW, int[], double[], int[], int[], intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dlaed9(int, int, int, int, double[], double[], int, double, double[], double[], double[], int, intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dlaeda(int, int, int, int, int[], int[], int[], int[], double[], double[], int[], double[], double[], intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dlaein(boolean, boolean, int, double[], int, double, double, double[], double[], double[], int, double[], double, double, double, intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dlaev2(double, double, double, doubleW, doubleW, doubleW, doubleW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dlaexc(boolean, int, double[], int, double[], int, int, int, int, double[], intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dlag2(double[], int, double[], int, double, doubleW, doubleW, doubleW, doubleW, doubleW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dlag2s(int, int, double[], int, float[], int, intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dlags2(boolean, double, double, double, double, double, double, doubleW, doubleW, doubleW, doubleW, doubleW, doubleW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dlagtf(int, double[], double, double[], double[], double, double[], int[], intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dlagtm(String, int, int, double, double[], double[], double[], double[], int, double, double[], int) -
Method in class org.netlib.lapack.LAPACK
-
..
- dlagts(int, int, double[], double[], double[], double[], int[], double[], doubleW, intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dlagv2(double[], int, double[], int, double[], double[], double[], doubleW, doubleW, doubleW, doubleW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dlahqr(boolean, boolean, int, int, int, double[], int, double[], double[], int, int, double[], int, intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dlahr2(int, int, int, double[], int, double[], double[], int, double[], int) -
Method in class org.netlib.lapack.LAPACK
-
..
- dlahrd(int, int, int, double[], int, double[], double[], int, double[], int) -
Method in class org.netlib.lapack.LAPACK
-
..
- dlaic1(int, int, double[], double, double[], double, doubleW, doubleW, doubleW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dlaisnan(double, double) -
Method in class org.netlib.lapack.LAPACK
-
..
- dlaln2(boolean, int, int, double, double, double[], int, double, double, double[], int, double, double, double[], int, doubleW, doubleW, intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dlals0(int, int, int, int, int, double[], int, double[], int, int[], int, int[], int, double[], int, double[], double[], double[], double[], int, double, double, double[], intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dlalsa(int, int, int, int, double[], int, double[], int, double[], int, double[], int[], double[], double[], double[], double[], int[], int[], int, int[], double[], double[], double[], double[], int[], intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dlalsd(String, int, int, int, double[], double[], double[], int, double, intW, double[], int[], intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dlamc1(intW, intW, booleanW, booleanW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dlamc2(intW, intW, booleanW, doubleW, intW, doubleW, intW, doubleW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dlamc3(double, double) -
Method in class org.netlib.lapack.LAPACK
-
..
- dlamc4(intW, double, int) -
Method in class org.netlib.lapack.LAPACK
-
..
- dlamc5(int, int, int, boolean, intW, doubleW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dlamch(String) -
Method in class org.netlib.lapack.LAPACK
-
..
- dlamrg(int, int, double[], int, int, int[]) -
Method in class org.netlib.lapack.LAPACK
-
..
- dlaneg(int, double[], double[], double, double, int) -
Method in class org.netlib.lapack.LAPACK
-
..
- dlangb(String, int, int, int, double[], int, double[]) -
Method in class org.netlib.lapack.LAPACK
-
..
- dlange(String, int, int, double[], int, double[]) -
Method in class org.netlib.lapack.LAPACK
-
..
- dlangt(String, int, double[], double[], double[]) -
Method in class org.netlib.lapack.LAPACK
-
..
- dlanhs(String, int, double[], int, double[]) -
Method in class org.netlib.lapack.LAPACK
-
..
- dlansb(String, String, int, int, double[], int, double[]) -
Method in class org.netlib.lapack.LAPACK
-
..
- dlansp(String, String, int, double[], double[]) -
Method in class org.netlib.lapack.LAPACK
-
..
- dlanst(String, int, double[], double[]) -
Method in class org.netlib.lapack.LAPACK
-
..
- dlansy(String, String, int, double[], int, double[]) -
Method in class org.netlib.lapack.LAPACK
-
..
- dlantb(String, String, String, int, int, double[], int, double[]) -
Method in class org.netlib.lapack.LAPACK
-
..
- dlantp(String, String, String, int, double[], double[]) -
Method in class org.netlib.lapack.LAPACK
-
..
- dlantr(String, String, String, int, int, double[], int, double[]) -
Method in class org.netlib.lapack.LAPACK
-
..
- dlanv2(doubleW, doubleW, doubleW, doubleW, doubleW, doubleW, doubleW, doubleW, doubleW, doubleW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dlapll(int, double[], int, double[], int, doubleW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dlapmt(boolean, int, int, double[], int, int[]) -
Method in class org.netlib.lapack.LAPACK
-
..
- dlapy2(double, double) -
Method in class org.netlib.lapack.LAPACK
-
..
- dlapy3(double, double, double) -
Method in class org.netlib.lapack.LAPACK
-
..
- dlaqgb(int, int, int, int, double[], int, double[], double[], double, double, double, StringW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dlaqge(int, int, double[], int, double[], double[], double, double, double, StringW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dlaqp2(int, int, int, double[], int, int[], double[], double[], double[], double[]) -
Method in class org.netlib.lapack.LAPACK
-
..
- dlaqps(int, int, int, int, intW, double[], int, int[], double[], double[], double[], double[], double[], int) -
Method in class org.netlib.lapack.LAPACK
-
..
- dlaqr0(boolean, boolean, int, int, int, double[], int, double[], double[], int, int, double[], int, double[], int, intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dlaqr1(int, double[], int, double, double, double, double, double[]) -
Method in class org.netlib.lapack.LAPACK
-
..
- dlaqr2(boolean, boolean, int, int, int, int, double[], int, int, int, double[], int, intW, intW, double[], double[], double[], int, int, double[], int, int, double[], int, double[], int) -
Method in class org.netlib.lapack.LAPACK
-
..
- dlaqr3(boolean, boolean, int, int, int, int, double[], int, int, int, double[], int, intW, intW, double[], double[], double[], int, int, double[], int, int, double[], int, double[], int) -
Method in class org.netlib.lapack.LAPACK
-
..
- dlaqr4(boolean, boolean, int, int, int, double[], int, double[], double[], int, int, double[], int, double[], int, intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dlaqr5(boolean, boolean, int, int, int, int, int, double[], double[], double[], int, int, int, double[], int, double[], int, double[], int, int, double[], int, int, double[], int) -
Method in class org.netlib.lapack.LAPACK
-
..
- dlaqrb(boolean, int, int, int, double[], int, double[], double[], double[], intW) -
Method in class org.netlib.arpack.ARPACK
- No documentation was available when generating this method.
- dlaqsb(String, int, int, double[], int, double[], double, double, StringW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dlaqsp(String, int, double[], double[], double, double, StringW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dlaqsy(String, int, double[], int, double[], double, double, StringW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dlaqtr(boolean, boolean, int, double[], int, double[], double, doubleW, double[], double[], intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dlar1v(int, int, int, double, double[], double[], double[], double[], double, double, double[], boolean, intW, doubleW, doubleW, intW, int[], doubleW, doubleW, doubleW, double[]) -
Method in class org.netlib.lapack.LAPACK
-
..
- dlar2v(int, double[], double[], double[], int, double[], double[], int) -
Method in class org.netlib.lapack.LAPACK
-
..
- dlarf(String, int, int, double[], int, double, double[], int, double[]) -
Method in class org.netlib.lapack.LAPACK
-
..
- dlarfb(String, String, String, String, int, int, int, double[], int, double[], int, double[], int, double[], int) -
Method in class org.netlib.lapack.LAPACK
-
..
- dlarfg(int, doubleW, double[], int, doubleW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dlarft(String, String, int, int, double[], int, double[], double[], int) -
Method in class org.netlib.lapack.LAPACK
-
..
- dlarfx(String, int, int, double[], double, double[], int, double[]) -
Method in class org.netlib.lapack.LAPACK
-
..
- dlargv(int, double[], int, double[], int, double[], int) -
Method in class org.netlib.lapack.LAPACK
-
..
- dlarnv(int, int[], int, double[]) -
Method in class org.netlib.lapack.LAPACK
-
..
- dlarra(int, double[], double[], double[], double, double, intW, int[], intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dlarrb(int, double[], double[], int, int, double, double, int, double[], double[], double[], double[], int[], double, double, int, intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dlarrc(String, int, double, double, double[], double[], double, intW, intW, intW, intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dlarrd(String, String, int, double, double, int, int, double[], double, double[], double[], double[], double, int, int[], intW, double[], double[], doubleW, doubleW, int[], int[], double[], int[], intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dlarre(String, int, doubleW, doubleW, int, int, double[], double[], double[], double, double, double, intW, int[], intW, double[], double[], double[], int[], int[], double[], doubleW, double[], int[], intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dlarrf(int, double[], double[], double[], int, int, double[], double[], double[], double, double, double, double, doubleW, double[], double[], double[], intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dlarrj(int, double[], double[], int, int, double, int, double[], double[], double[], int[], double, double, intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dlarrk(int, int, double, double, double[], double[], double, double, doubleW, doubleW, intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dlarrr(int, double[], double[], intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dlarrv(int, double, double, double[], double[], double, int[], int, int, int, double, doubleW, doubleW, double[], double[], double[], int[], int[], double[], double[], int, int[], double[], int[], intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dlartg(double, double, doubleW, doubleW, doubleW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dlartv(int, double[], int, double[], int, double[], double[], int) -
Method in class org.netlib.lapack.LAPACK
-
..
- dlaruv(int[], int, double[]) -
Method in class org.netlib.lapack.LAPACK
-
..
- dlarz(String, int, int, int, double[], int, double, double[], int, double[]) -
Method in class org.netlib.lapack.LAPACK
-
..
- dlarzb(String, String, String, String, int, int, int, int, double[], int, double[], int, double[], int, double[], int) -
Method in class org.netlib.lapack.LAPACK
-
..
- dlarzt(String, String, int, int, double[], int, double[], double[], int) -
Method in class org.netlib.lapack.LAPACK
-
..
- dlas2(double, double, double, doubleW, doubleW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dlascl(String, int, int, double, double, int, int, double[], int, intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dlasd0(int, int, double[], double[], double[], int, double[], int, int, int[], double[], intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dlasd1(int, int, int, double[], doubleW, doubleW, double[], int, double[], int, int[], int[], double[], intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dlasd2(int, int, int, intW, double[], double[], double, double, double[], int, double[], int, double[], double[], int, double[], int, int[], int[], int[], int[], int[], intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dlasd3(int, int, int, int, double[], double[], int, double[], double[], int, double[], int, double[], int, double[], int, int[], int[], double[], intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dlasd4(int, int, double[], double[], double[], double, doubleW, double[], intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dlasd5(int, double[], double[], double[], double, doubleW, double[]) -
Method in class org.netlib.lapack.LAPACK
-
..
- dlasd6(int, int, int, int, double[], double[], double[], doubleW, doubleW, int[], int[], intW, int[], int, double[], int, double[], double[], double[], double[], intW, doubleW, doubleW, double[], int[], intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dlasd7(int, int, int, int, intW, double[], double[], double[], double[], double[], double[], double[], double, double, double[], int[], int[], int[], int[], intW, int[], int, double[], int, doubleW, doubleW, intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dlasd8(int, int, double[], double[], double[], double[], double[], double[], int, double[], double[], intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dlasda(int, int, int, int, double[], double[], double[], int, double[], int[], double[], double[], double[], double[], int[], int[], int, int[], double[], double[], double[], double[], int[], intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dlasdq(String, int, int, int, int, int, double[], double[], double[], int, double[], int, double[], int, double[], intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dlasdt(int, intW, intW, int[], int[], int[], int) -
Method in class org.netlib.lapack.LAPACK
-
..
- dlaset(String, int, int, double, double, double[], int) -
Method in class org.netlib.lapack.LAPACK
-
..
- dlasq1(int, double[], double[], double[], intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dlasq2(int, double[], intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dlasq3(int, intW, double[], int, doubleW, doubleW, doubleW, doubleW, intW, intW, intW, boolean) -
Method in class org.netlib.lapack.LAPACK
-
..
- dlasq4(int, int, double[], int, int, double, double, double, double, double, double, doubleW, intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dlasq5(int, int, double[], int, double, doubleW, doubleW, doubleW, doubleW, doubleW, doubleW, boolean) -
Method in class org.netlib.lapack.LAPACK
-
..
- dlasq6(int, int, double[], int, doubleW, doubleW, doubleW, doubleW, doubleW, doubleW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dlasr(String, String, String, int, int, double[], double[], double[], int) -
Method in class org.netlib.lapack.LAPACK
-
..
- dlasrt(String, int, double[], intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dlassq(int, double[], int, doubleW, doubleW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dlasv2(double, double, double, doubleW, doubleW, doubleW, doubleW, doubleW, doubleW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dlaswp(int, double[], int, int, int, int[], int) -
Method in class org.netlib.lapack.LAPACK
-
..
- dlasy2(boolean, boolean, int, int, int, double[], int, double[], int, double[], int, doubleW, double[], int, doubleW, intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dlasyf(String, int, int, intW, double[], int, int[], double[], int, intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dlatbs(String, String, String, String, int, int, double[], int, double[], doubleW, double[], intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dlatdf(int, int, double[], int, double[], doubleW, doubleW, int[], int[]) -
Method in class org.netlib.lapack.LAPACK
-
..
- dlatps(String, String, String, String, int, double[], double[], doubleW, double[], intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dlatrd(String, int, int, double[], int, double[], double[], double[], int) -
Method in class org.netlib.lapack.LAPACK
-
..
- dlatrs(String, String, String, String, int, double[], int, double[], doubleW, double[], intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dlatrz(int, int, int, double[], int, double[], double[]) -
Method in class org.netlib.lapack.LAPACK
-
..
- dlatzm(String, int, int, double[], int, double, double[], double[], int, double[]) -
Method in class org.netlib.lapack.LAPACK
-
..
- dlauu2(String, int, double[], int, intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dlauum(String, int, double[], int, intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dlazq3(int, intW, double[], int, doubleW, doubleW, doubleW, doubleW, intW, intW, intW, boolean, intW, doubleW, doubleW, doubleW, doubleW, doubleW, doubleW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dlazq4(int, int, double[], int, int, double, double, double, double, double, double, doubleW, intW, doubleW) -
Method in class org.netlib.lapack.LAPACK
-
..
- DMatrix - Class in umontreal.iro.lecuyer.util
- This class implements a few methods for matrix calculations
with double numbers.
- DMatrix(int, int) -
Constructor for class umontreal.iro.lecuyer.util.DMatrix
- Creates a new DMatrix with r rows and
c columns.
- DMatrix(double[][], int, int) -
Constructor for class umontreal.iro.lecuyer.util.DMatrix
- Creates a new DMatrix with r rows and
c columns using the data in data.
- DMatrix(DMatrix) -
Constructor for class umontreal.iro.lecuyer.util.DMatrix
- Copy constructor.
- dmout(int, int, int, double[], int, int, String) -
Method in class org.netlib.arpack.ARPACK
- No documentation was available when generating this method.
- dnaitr(intW, String, int, int, int, int, double[], doubleW, double[], int, double[], int, int[], double[], intW) -
Method in class org.netlib.arpack.ARPACK
- No documentation was available when generating this method.
- dnapps(int, intW, int, double[], double[], double[], int, double[], int, double[], double[], int, double[], double[]) -
Method in class org.netlib.arpack.ARPACK
- No documentation was available when generating this method.
- dnaup2(intW, String, int, String, intW, intW, double, double[], int, int, int, intW, double[], int, double[], int, double[], double[], double[], double[], int, double[], int[], double[], intW) -
Method in class org.netlib.arpack.ARPACK
- No documentation was available when generating this method.
- dnaupd(intW, String, int, String, int, doubleW, double[], int, double[], int, int[], int[], double[], double[], int, intW) -
Method in class org.netlib.arpack.ARPACK
- No documentation was available when generating this method.
- dnconv(int, double[], double[], double[], double, intW) -
Method in class org.netlib.arpack.ARPACK
- No documentation was available when generating this method.
- dneigh(double, intW, double[], int, double[], double[], double[], double[], int, double[], intW) -
Method in class org.netlib.arpack.ARPACK
- No documentation was available when generating this method.
- dneupd(boolean, String, boolean[], double[], double[], double[], int, double, double, double[], String, int, String, intW, double, double[], int, double[], int, int[], int[], double[], double[], int, intW) -
Method in class org.netlib.arpack.ARPACK
- No documentation was available when generating this method.
- dngets(int, String, intW, intW, double[], double[], double[], double[], double[]) -
Method in class org.netlib.arpack.ARPACK
- No documentation was available when generating this method.
- dnrm2(DoubleMatrix1D) -
Method in interface cern.colt.matrix.linalg.Blas
- Return the 2-norm; sqrt(x[0]^2 + x[1]^2 + ...).
- dnrm2(DoubleMatrix1D) -
Method in class cern.colt.matrix.linalg.SeqBlas
-
- dnrm2(DoubleMatrix1D) -
Method in class cern.colt.matrix.linalg.SmpBlas
-
- dnrm2(DoubleMatrix1D) -
Method in interface cern.colt.matrix.tdouble.algo.DoubleBlas
- Return the 2-norm; sqrt(x[0]^2 + x[1]^2 + ...).
- dnrm2(DoubleMatrix1D) -
Method in class cern.colt.matrix.tdouble.algo.SmpDoubleBlas
-
- dnrm2(FloatMatrix1D) -
Method in interface cern.colt.matrix.tfloat.algo.FloatBlas
- Return the 2-norm; sqrt(x[0]^2 + x[1]^2 + ...).
- dnrm2(FloatMatrix1D) -
Method in class cern.colt.matrix.tfloat.algo.SmpFloatBlas
-
- dnrm2(int, double[], int) -
Method in class org.netlib.blas.BLAS
-
..
- doc() -
Method in class jhplot.F1D
- Show online documentation.
- doc() -
Method in class jhplot.F2D
- Show online documentation.
- doc() -
Method in class jhplot.F3D
- Show online documentation.
- doc() -
Method in class jhplot.FND
- Show online documentation.
- doc() -
Method in class jhplot.H1D
- Show online documentation.
- doc() -
Method in class jhplot.H2D
- Show online documentation.
- doc() -
Method in class jhplot.H3D
- Show online documentation.
- doc() -
Method in class jhplot.HBayes
-
- doc() -
Method in class jhplot.HBook
- Show online documentation.
- doc() -
Method in class jhplot.HBsom
- Show documentation
- doc() -
Method in class jhplot.HCellular
- Show documentation
- doc() -
Method in class jhplot.HChart
- Show online documentation.
- doc() -
Method in class jhplot.HCluster
- Show online documentation.
- doc() -
Method in class jhplot.HFit
- Show online documentation.
- doc() -
Method in class jhplot.HFitter
- Show online documentation.
- doc() -
Method in class jhplot.HGraph
- Show online documentation.
- doc() -
Method in class jhplot.HLabel
- Show online documentation.
- doc() -
Method in class jhplot.HLabelEq
- Show online documentation.
- doc() -
Method in class jhplot.HMLabel
- Show online documentation.
- doc() -
Method in class jhplot.HNeuralNet
- Show online documentation.
- doc() -
Method in class jhplot.HPlot
- Show online documentation.
- doc() -
Method in class jhplot.HPlot2D
- Show online documentation.
- doc() -
Method in class jhplot.HPlot3D
- Show online documentation.
- doc() -
Method in class jhplot.HPlot3DP
- Show online documentation.
- doc() -
Method in class jhplot.HPlotJa
- Show online documentation.
- doc() -
Method in class jhplot.HProf1D
- Show online documentation.
- doc() -
Method in class jhplot.HProf2D
- Show online documentation.
- doc() -
Method in class jhplot.HTable
- Show online documentation.
- doc() -
Method in class jhplot.HView3D
- Show online documentation.
- doc() -
Method in class jhplot.IEditor
- Show online documentation.
- doc() -
Method in class jhplot.io.csv.CSVReader
- Show online documentation.
- doc() -
Method in class jhplot.io.csv.CSVWriter
- Show online documentation.
- doc() -
Method in class jhplot.io.FileAida
- Show online documentation.
- doc() -
Method in class jhplot.io.FileRoot
- Show online documentation.
- doc() -
Method in class jhplot.IView
- Show online documentation.
- doc() -
Method in class jhplot.JHPlot
- Show online documentation.
- doc() -
Method in class jhplot.P0D
- Show online documentation.
- doc() -
Method in class jhplot.P0I
- Show online documentation.
- doc() -
Method in class jhplot.P1D
- Show online documentation.
- doc() -
Method in class jhplot.P2D
- Show online documentation.
- doc() -
Method in class jhplot.P3D
- Show online documentation.
- doc() -
Method in class jhplot.PND
- Show online documentation.
- doc() -
Method in class jhplot.PNI
- Show online documentation.
- doc() -
Method in class jhplot.shapes.Arrow
- Show online documentation.
- doc() -
Method in class jhplot.shapes.Circle
- Show online documentation.
- doc() -
Method in class jhplot.shapes.Ellipse
- Show online documentation.
- doc() -
Method in class jhplot.shapes.Line
- Show online documentation.
- doc() -
Method in class jhplot.shapes.Picture
- Show online documentation.
- doc() -
Method in class jhplot.shapes.Rectan
- Show online documentation.
- doc() -
Method in class jhplot.shapes.Text
- Show online documentation.
- doc() -
Method in class jhplot.SHPlot
- Show online documentation.
- doc() -
Method in class jhplot.SHPlot3D
- Show online documentation.
- doc() -
Method in class jhplot.SHPlotJa
- Show online documentation.
- doc() -
Method in class jhplot.SPlot
- Show online documentation.
- doc() -
Method in class jhplot.SPsheet
- Show online documentation.
- doc() -
Method in class jhplot.stat.BunchingParameters
- Show online documentation.
- doc() -
Method in class jhplot.stat.FactorialMoments
- Show online documentation.
- doc() -
Method in class jhplot.stat.LinReg
- Show online documentation.
- doc() -
Method in class jhplot.stat.LinRegWeighted
- Show online documentation.
- doc() -
Method in class jhplot.stat.PCA
- Show online documentation.
- doc() -
Method in class jhplot.stat.Statistics
- Show online documentation.
- doc() -
Method in class jhplot.stat.StatShape
- Show online documentation.
- doc() -
Method in class jhplot.VHolder
- Show online documentation.
- doc() -
Method in class jhpro.stat.CLimits
- Show online documentation.
- doc() -
Method in class jhpro.stat.ConfidenceLevel
- Show online documentation.
- doc() -
Method in class jhpro.stat.EEcentricity
- Show online documentation.
- doc() -
Method in class jhpro.stat.Moments
- Show online documentation.
- doc() -
Method in class jhpro.stat.MomentsFac
- Show online documentation.
- doc() -
Method in class jhpro.stat.MomentsFacNorm
- Show online documentation.
- doc() -
Method in class jhpro.stat.MomentsNorm
- Show online documentation.
- doOptimize() -
Method in class org.apache.commons.math.optimization.general.GaussNewtonOptimizer
- Perform the bulk of optimization algorithm.
- doOptimize() -
Method in class org.apache.commons.math.optimization.linear.SimplexSolver
- Perform the bulk of optimization algorithm.
- dopgtr(String, int, double[], double[], double[], int, double[], intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dopmtr(String, String, String, int, int, double[], double[], double[], int, double[], intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dorg2l(int, int, int, double[], int, double[], double[], intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dorg2r(int, int, int, double[], int, double[], double[], intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dorgbr(String, int, int, int, double[], int, double[], double[], int, intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dorghr(int, int, int, double[], int, double[], double[], int, intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dorgl2(int, int, int, double[], int, double[], double[], intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dorglq(int, int, int, double[], int, double[], double[], int, intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dorgql(int, int, int, double[], int, double[], double[], int, intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dorgqr(int, int, int, double[], int, double[], double[], int, intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dorgr2(int, int, int, double[], int, double[], double[], intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dorgrq(int, int, int, double[], int, double[], double[], int, intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dorgtr(String, int, double[], int, double[], double[], int, intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dorm2l(String, String, int, int, int, double[], int, double[], double[], int, double[], intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dorm2r(String, String, int, int, int, double[], int, double[], double[], int, double[], intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- DormandPrince54Integrator - Class in org.apache.commons.math.ode.nonstiff
- This class implements the 5(4) Dormand-Prince integrator for Ordinary
Differential Equations.
- DormandPrince54Integrator(double, double, double, double) -
Constructor for class org.apache.commons.math.ode.nonstiff.DormandPrince54Integrator
- Simple constructor.
- DormandPrince54Integrator(double, double, double[], double[]) -
Constructor for class org.apache.commons.math.ode.nonstiff.DormandPrince54Integrator
- Simple constructor.
- DormandPrince853Integrator - Class in org.apache.commons.math.ode.nonstiff
- This class implements the 8(5,3) Dormand-Prince integrator for Ordinary
Differential Equations.
- DormandPrince853Integrator(double, double, double, double) -
Constructor for class org.apache.commons.math.ode.nonstiff.DormandPrince853Integrator
- Simple constructor.
- DormandPrince853Integrator(double, double, double[], double[]) -
Constructor for class org.apache.commons.math.ode.nonstiff.DormandPrince853Integrator
- Simple constructor.
- dormbr(String, String, String, int, int, int, double[], int, double[], double[], int, double[], int, intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dormhr(String, String, int, int, int, int, double[], int, double[], double[], int, double[], int, intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dorml2(String, String, int, int, int, double[], int, double[], double[], int, double[], intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dormlq(String, String, int, int, int, double[], int, double[], double[], int, double[], int, intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dormql(String, String, int, int, int, double[], int, double[], double[], int, double[], int, intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dormqr(String, String, int, int, int, double[], int, double[], double[], int, double[], int, intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dormr2(String, String, int, int, int, double[], int, double[], double[], int, double[], intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dormr3(String, String, int, int, int, int, double[], int, double[], double[], int, double[], intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dormrq(String, String, int, int, int, double[], int, double[], double[], int, double[], int, intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dormrz(String, String, int, int, int, int, double[], int, double[], double[], int, double[], int, intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dormtr(String, String, String, int, int, double[], int, double[], double[], int, double[], int, intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dot(Hep3Vector, Hep3Vector) -
Method in class hephysics.vec.Hep3Vector
- Dot product of 2 vectors
- dot(Hep3Vector) -
Method in class hephysics.vec.Hep3Vector
- Dot operation
- dot(HepLorentzVector, HepLorentzVector) -
Method in class hephysics.vec.HepLorentzVector
- Dot product
- dot(Hep3Vector, Hep3Vector) -
Static method in class hephysics.vec.VecOp
-
- dot(Vector3d) -
Method in class jhplot.v3d.Vector3d
-
- dotProduct(Vector3D, Vector3D) -
Static method in class org.apache.commons.math.geometry.Vector3D
- Compute the dot-product of two vectors.
- dotProduct(double[]) -
Method in class org.apache.commons.math.linear.AbstractRealVector
- Compute the dot product.
- dotProduct(RealVector) -
Method in class org.apache.commons.math.linear.AbstractRealVector
- Compute the dot product.
- dotProduct(FieldVector<T>) -
Method in class org.apache.commons.math.linear.ArrayFieldVector
- Compute the dot product.
- dotProduct(T[]) -
Method in class org.apache.commons.math.linear.ArrayFieldVector
- Compute the dot product.
- dotProduct(ArrayFieldVector<T>) -
Method in class org.apache.commons.math.linear.ArrayFieldVector
- Compute the dot product.
- dotProduct(RealVector) -
Method in class org.apache.commons.math.linear.ArrayRealVector
- Compute the dot product.
- dotProduct(double[]) -
Method in class org.apache.commons.math.linear.ArrayRealVector
- Compute the dot product.
- dotProduct(ArrayRealVector) -
Method in class org.apache.commons.math.linear.ArrayRealVector
- Compute the dot product.
- dotProduct(FieldVector<T>) -
Method in interface org.apache.commons.math.linear.FieldVector
- Compute the dot product.
- dotProduct(T[]) -
Method in interface org.apache.commons.math.linear.FieldVector
- Compute the dot product.
- dotProduct(OpenMapRealVector) -
Method in class org.apache.commons.math.linear.OpenMapRealVector
- Optimized method to compute the dot product with an OpenMapRealVector.
- dotProduct(RealVector) -
Method in class org.apache.commons.math.linear.OpenMapRealVector
- Compute the dot product.
- dotProduct(RealVector) -
Method in interface org.apache.commons.math.linear.RealVector
- Compute the dot product.
- dotProduct(double[]) -
Method in interface org.apache.commons.math.linear.RealVector
- Compute the dot product.
- dotProduct(FieldVector<T>) -
Method in class org.apache.commons.math.linear.SparseFieldVector
- Compute the dot product.
- dotProduct(T[]) -
Method in class org.apache.commons.math.linear.SparseFieldVector
- Compute the dot product.
- dotrap(int, String, Dfp, Dfp) -
Method in class org.apache.commons.math.dfp.Dfp
- Raises a trap.
- Double27Function - Interface in cern.colt.function
- Interface that represents a function object: a function that takes
27 arguments and returns a single value.
- Double27Function - Interface in cern.colt.function.tdouble
- Interface that represents a function object: a function that takes 27
arguments and returns a single value.
- Double5Function - Interface in cern.colt.function
- Interface that represents a function object: a function that takes
5 arguments and returns a single value.
- Double5Function - Interface in cern.colt.function.tdouble
- Interface that represents a function object: a function that takes 5
arguments and returns a single value.
- Double9Function - Interface in cern.colt.function
- Interface that represents a function object: a function that takes
9 arguments and returns a single value.
- Double9Function - Interface in cern.colt.function.tdouble
- Interface that represents a function object: a function that takes 9
arguments and returns a single value.
- DoubleAMG - Class in cern.colt.matrix.tdouble.algo.solver.preconditioner
- Algebraic multigrid preconditioner.
- DoubleAMG(double, double, double, double, int, int, int, int, double) -
Constructor for class cern.colt.matrix.tdouble.algo.solver.preconditioner.DoubleAMG
- Sets up the algebraic multigrid preconditioner
- DoubleAMG(double, double, int, int, int, int, double) -
Constructor for class cern.colt.matrix.tdouble.algo.solver.preconditioner.DoubleAMG
- Sets up the algebraic multigrid preconditioner.
- DoubleAMG() -
Constructor for class cern.colt.matrix.tdouble.algo.solver.preconditioner.DoubleAMG
- Sets up the algebraic multigrid preconditioner using some default
parameters.
- DoubleArithmetic - Class in cern.jet.math.tdouble
- Arithmetic functions.
- doubleArray(int) -
Method in class flanagan.math.PsRandom
-
- doubleArray(int, double) -
Method in class flanagan.math.PsRandom
-
- doubleArray(int, double, double) -
Method in class flanagan.math.PsRandom
-
- DoubleArray - Class in jhplot.math
- A class for dealing with double arrays and matrices.
- DoubleArray() -
Constructor for class jhplot.math.DoubleArray
-
- DoubleArray - Class in jhplot.math.num
- An expandable double array.
- DoubleArray() -
Constructor for class jhplot.math.num.DoubleArray
-
- DoubleArray - Interface in org.apache.commons.math.util
- Provides a standard interface for double arrays.
- DoubleArrayComparator - Class in umontreal.iro.lecuyer.util
- An implementation of
Comparator
which compares two
double arrays by comparing their i-th element,
where i is given in the constructor. - DoubleArrayComparator(int) -
Constructor for class umontreal.iro.lecuyer.util.DoubleArrayComparator
- Constructs a comparator, where i is the index
used for the comparisons.
- DoubleArrayList - Class in cern.colt.list
- Resizable list holding
double
elements; implemented with arrays. - DoubleArrayList() -
Constructor for class cern.colt.list.DoubleArrayList
- Constructs an empty list.
- DoubleArrayList(double[]) -
Constructor for class cern.colt.list.DoubleArrayList
- Constructs a list containing the specified elements.
- DoubleArrayList(int) -
Constructor for class cern.colt.list.DoubleArrayList
- Constructs an empty list with the specified initial capacity.
- DoubleArrayList - Class in cern.colt.list.tdouble
- Resizable list holding
double
elements; implemented with arrays. - DoubleArrayList() -
Constructor for class cern.colt.list.tdouble.DoubleArrayList
- Constructs an empty list.
- DoubleArrayList(double[]) -
Constructor for class cern.colt.list.tdouble.DoubleArrayList
- Constructs a list containing the specified elements.
- DoubleArrayList(int) -
Constructor for class cern.colt.list.tdouble.DoubleArrayList
- Constructs an empty list with the specified initial capacity.
- DoubleBiCG - Class in cern.colt.matrix.tdouble.algo.solver
- BiCG solver.
- DoubleBiCG(DoubleMatrix1D) -
Constructor for class cern.colt.matrix.tdouble.algo.solver.DoubleBiCG
- Constructor for BiCG.
- DoubleBiCGstab - Class in cern.colt.matrix.tdouble.algo.solver
- BiCG stablized solver.
- DoubleBiCGstab(DoubleMatrix1D) -
Constructor for class cern.colt.matrix.tdouble.algo.solver.DoubleBiCGstab
- Constructor for BiCGstab.
- DoubleBinBinFunction1D - Interface in hep.aida.tdouble.bin
- Interface that represents a function object: a function that takes two bins
as arguments and returns a single value.
- DoubleBinFunction1D - Interface in hep.aida.tdouble.bin
- Interface that represents a function object: a function that takes two bins
as arguments and returns a single value.
- DoubleBinFunctions1D - Class in hep.aida.tdouble.bin
- Function objects computing dynamic bin aggregations; to be passed to generic
methods.
- DoubleBlas - Interface in cern.colt.matrix.tdouble.algo
-
Subset of the BLAS
(Basic Linear Algebra System); High quality "building block" routines for
performing basic vector and matrix operations.
- DoubleBuffer - Class in cern.colt.buffer
- Fixed sized (non resizable) streaming buffer connected to a target DoubleBufferConsumer to which data is automatically flushed upon buffer overflow.
- DoubleBuffer(DoubleBufferConsumer, int) -
Constructor for class cern.colt.buffer.DoubleBuffer
- Constructs and returns a new buffer with the given target.
- DoubleBuffer - Class in cern.colt.buffer.tdouble
- Fixed sized (non resizable) streaming buffer connected to a target
DoubleBufferConsumer to which data is automatically flushed upon
buffer overflow.
- DoubleBuffer(DoubleBufferConsumer, int) -
Constructor for class cern.colt.buffer.tdouble.DoubleBuffer
- Constructs and returns a new buffer with the given target.
- DoubleBuffer - Class in cern.jet.stat.tdouble.quantile
- A buffer holding double elements; internally used for computing
approximate quantiles.
- DoubleBuffer(int) -
Constructor for class cern.jet.stat.tdouble.quantile.DoubleBuffer
- This method was created in VisualAge.
- DoubleBuffer2D - Class in cern.colt.buffer
- Fixed sized (non resizable) streaming buffer connected to a target DoubleBuffer2DConsumer to which data is automatically flushed upon buffer overflow.
- DoubleBuffer2D(DoubleBuffer2DConsumer, int) -
Constructor for class cern.colt.buffer.DoubleBuffer2D
- Constructs and returns a new buffer with the given target.
- DoubleBuffer2D - Class in cern.colt.buffer.tdouble
- Fixed sized (non resizable) streaming buffer connected to a target
DoubleBuffer2DConsumer to which data is automatically flushed upon
buffer overflow.
- DoubleBuffer2D(DoubleBuffer2DConsumer, int) -
Constructor for class cern.colt.buffer.tdouble.DoubleBuffer2D
- Constructs and returns a new buffer with the given target.
- DoubleBuffer2DConsumer - Interface in cern.colt.buffer
- Target of a streaming DoubleBuffer2D into which data is flushed upon buffer overflow.
- DoubleBuffer2DConsumer - Interface in cern.colt.buffer.tdouble
- Target of a streaming DoubleBuffer2D into which data is flushed upon
buffer overflow.
- DoubleBuffer3D - Class in cern.colt.buffer
- Fixed sized (non resizable) streaming buffer connected to a target DoubleBuffer3DConsumer to which data is automatically flushed upon buffer overflow.
- DoubleBuffer3D(DoubleBuffer3DConsumer, int) -
Constructor for class cern.colt.buffer.DoubleBuffer3D
- Constructs and returns a new buffer with the given target.
- DoubleBuffer3D - Class in cern.colt.buffer.tdouble
- Fixed sized (non resizable) streaming buffer connected to a target
DoubleBuffer3DConsumer to which data is automatically flushed upon
buffer overflow.
- DoubleBuffer3D(DoubleBuffer3DConsumer, int) -
Constructor for class cern.colt.buffer.tdouble.DoubleBuffer3D
- Constructs and returns a new buffer with the given target.
- DoubleBuffer3DConsumer - Interface in cern.colt.buffer
- Target of a streaming DoubleBuffer3D into which data is flushed upon buffer overflow.
- DoubleBuffer3DConsumer - Interface in cern.colt.buffer.tdouble
- Target of a streaming DoubleBuffer3D into which data is flushed upon
buffer overflow.
- DoubleBufferConsumer - Interface in cern.colt.buffer
- Target of a streaming DoubleBuffer into which data is flushed upon buffer overflow.
- DoubleBufferConsumer - Interface in cern.colt.buffer.tdouble
- Target of a streaming DoubleBuffer into which data is flushed upon
buffer overflow.
- DoubleCG - Class in cern.colt.matrix.tdouble.algo.solver
- Conjugate Gradients solver.
- DoubleCG(DoubleMatrix1D) -
Constructor for class cern.colt.matrix.tdouble.algo.solver.DoubleCG
- Constructor for CG.
- DoubleCGLS - Class in cern.colt.matrix.tdouble.algo.solver
- CGLS is Conjugate Gradient for Least Squares method used for solving
large-scale, ill-posed inverse problems of the form: b = A*x + noise.
- DoubleCGLS() -
Constructor for class cern.colt.matrix.tdouble.algo.solver.DoubleCGLS
-
- DoubleCGS - Class in cern.colt.matrix.tdouble.algo.solver
- Conjugate Gradients squared solver.
- DoubleCGS(DoubleMatrix1D) -
Constructor for class cern.colt.matrix.tdouble.algo.solver.DoubleCGS
- Constructor for CGS.
- DoubleChebyshev - Class in cern.colt.matrix.tdouble.algo.solver
- Chebyshev solver.
- DoubleChebyshev(DoubleMatrix1D, double, double) -
Constructor for class cern.colt.matrix.tdouble.algo.solver.DoubleChebyshev
- Constructor for Chebyshev.
- DoubleComparator - Interface in cern.colt.function
- A comparison function which imposes a total ordering on some
collection of elements.
- DoubleComparator - Interface in cern.colt.function.tdouble
- A comparison function which imposes a total ordering on some
collection of elements.
- DoubleConstants - Class in cern.jet.math.tdouble
- Defines some useful constants.
- DoubleConverter - Class in hep.aida.tdouble.ref
- Histogram conversions, for example to String and XML format; This class
requires the Colt distribution, whereas the rest of the package is entirelly
stand-alone.
- DoubleConverter() -
Constructor for class hep.aida.tdouble.ref.DoubleConverter
- Creates a new histogram converter.
- DoubleDescriptive - Class in cern.jet.stat.tdouble
- Basic descriptive statistics.
- DoubleDiagonal - Class in cern.colt.matrix.tdouble.algo.solver.preconditioner
- Diagonal preconditioner.
- DoubleDiagonal(int) -
Constructor for class cern.colt.matrix.tdouble.algo.solver.preconditioner.DoubleDiagonal
- Constructor for DiagonalPreconditioner
- DoubleDoubleFunction - Interface in cern.colt.function
- Interface that represents a function object: a function that takes
two arguments and returns a single value.
- DoubleDoubleFunction - Interface in cern.colt.function.tdouble
- Interface that represents a function object: a function that takes two
arguments and returns a single value.
- DoubleDoubleProcedure - Interface in cern.colt.function
- Interface that represents a procedure object: a procedure that takes
two arguments and does not return a value.
- DoubleDoubleProcedure - Interface in cern.colt.function.tdouble
- Interface that represents a procedure object: a procedure that takes two
arguments and does not return a value.
- DoubleEquiDepthHistogram - Class in cern.jet.stat.tdouble.quantile
- Read-only equi-depth histogram for selectivity estimation.
- DoubleEquiDepthHistogram(double[]) -
Constructor for class cern.jet.stat.tdouble.quantile.DoubleEquiDepthHistogram
- Constructs an equi-depth histogram with the given quantile elements.
- DoubleFactory1D - Class in cern.colt.matrix
- Factory for convenient construction of 1-d matrices holding double cells.
- DoubleFactory1D - Class in cern.colt.matrix.tdouble
- Factory for convenient construction of 1-d matrices holding double
cells.
- DoubleFactory2D - Class in cern.colt.matrix
- Factory for convenient construction of 2-d matrices holding double
cells.
- DoubleFactory2D - Class in cern.colt.matrix.tdouble
- Factory for convenient construction of 2-d matrices holding double
cells.
- DoubleFactory3D - Class in cern.colt.matrix
- Factory for convenient construction of 3-d matrices holding double cells.
- DoubleFactory3D - Class in cern.colt.matrix.tdouble
- Factory for convenient construction of 3-d matrices holding double
cells.
- DoubleFixedAxis - Class in hep.aida.tdouble.ref
- Fixed-width axis; A reference implementation of hep.aida.IAxis.
- DoubleFixedAxis(int, double, double) -
Constructor for class hep.aida.tdouble.ref.DoubleFixedAxis
- Create an Axis
- DoubleFormatter - Class in cern.colt.matrix.tdouble.algo
- Flexible, well human readable matrix print formatting; By default decimal
point aligned.
- DoubleFormatter() -
Constructor for class cern.colt.matrix.tdouble.algo.DoubleFormatter
- Constructs and returns a matrix formatter with format "%G".
- DoubleFormatter(String) -
Constructor for class cern.colt.matrix.tdouble.algo.DoubleFormatter
- Constructs and returns a matrix formatter.
- DoubleFunction - Interface in cern.colt.function
- Interface that represents a function object: a function that takes
a single argument and returns a single value.
- DoubleFunction - Interface in cern.colt.function.tdouble
- Interface that represents a function object: a function that takes a single
argument and returns a single value.
- DoubleFunctions - Class in cern.jet.math.tdouble
- Function objects to be passed to generic methods.
- DoubleGivensRotation - Class in cern.colt.matrix.tdouble.algo.solver
- Givens plane rotation
- DoubleGivensRotation(double, double) -
Constructor for class cern.colt.matrix.tdouble.algo.solver.DoubleGivensRotation
- Constructs a Givens plane rotation for a given 2-vector
- DoubleGMRES - Class in cern.colt.matrix.tdouble.algo.solver
- GMRES solver.
- DoubleGMRES(DoubleMatrix1D) -
Constructor for class cern.colt.matrix.tdouble.algo.solver.DoubleGMRES
- Constructor for GMRES.
- DoubleGMRES(DoubleMatrix1D, int) -
Constructor for class cern.colt.matrix.tdouble.algo.solver.DoubleGMRES
- Constructor for GMRES.
- DoubleHistogram1D - Class in hep.aida.tdouble.ref
- A reference implementation of hep.aida.IHistogram1D.
- DoubleHistogram1D(String, double[]) -
Constructor for class hep.aida.tdouble.ref.DoubleHistogram1D
- Creates a variable-width histogram.
- DoubleHistogram1D(String, DoubleIAxis) -
Constructor for class hep.aida.tdouble.ref.DoubleHistogram1D
- Creates a histogram with the given axis binning.
- DoubleHistogram1D(String, int, double, double) -
Constructor for class hep.aida.tdouble.ref.DoubleHistogram1D
- Creates a fixed-width histogram.
- DoubleHistogram1DContents - Class in hep.aida.tdouble.ref
-
- DoubleHistogram1DContents(int[], double[], double[], int, double, double, double, double) -
Constructor for class hep.aida.tdouble.ref.DoubleHistogram1DContents
-
- DoubleHistogram2D - Class in hep.aida.tdouble.ref
- A reference implementation of hep.aida.IHistogram2D.
- DoubleHistogram2D(String, double[], double[]) -
Constructor for class hep.aida.tdouble.ref.DoubleHistogram2D
- Creates a variable-width histogram.
- DoubleHistogram2D(String, int, double, double, int, double, double) -
Constructor for class hep.aida.tdouble.ref.DoubleHistogram2D
- Creates a fixed-width histogram.
- DoubleHistogram2D(String, DoubleIAxis, DoubleIAxis) -
Constructor for class hep.aida.tdouble.ref.DoubleHistogram2D
- Creates a histogram with the given axis binning.
- DoubleHistogram3D - Class in hep.aida.tdouble.ref
- A reference implementation of hep.aida.IHistogram3D.
- DoubleHistogram3D(String, double[], double[], double[]) -
Constructor for class hep.aida.tdouble.ref.DoubleHistogram3D
- Creates a variable-width histogram.
- DoubleHistogram3D(String, int, double, double, int, double, double, int, double, double) -
Constructor for class hep.aida.tdouble.ref.DoubleHistogram3D
- Creates a fixed-width histogram.
- DoubleHistogram3D(String, DoubleIAxis, DoubleIAxis, DoubleIAxis) -
Constructor for class hep.aida.tdouble.ref.DoubleHistogram3D
- Creates a histogram with the given axis binning.
- DoubleHyBR - Class in cern.colt.matrix.tdouble.algo.solver
- HyBR is a Hybrid Bidiagonalization Regularization method used for solving
large-scale, ill-posed inverse problems of the form: b = A*x + noise The
method combines an iterative Lanczos Bidiagonalization (LBD) Method with an
SVD-based regularization method to stabilize the semiconvergence behavior
that is characteristic of many ill-posed problems.
- DoubleHyBR() -
Constructor for class cern.colt.matrix.tdouble.algo.solver.DoubleHyBR
- Creates new instance of HyBR solver with default parameters:
innerSolver = HyBR.InnerSolver.TIKHONOV
regularizationMethod = HyBR.RegularizationMethod.ADAPTWGCV
regularizationParameter = 0
omega = 0
reorthogonalize = false
beginRegularization = 2
flatTolerance = 1e-6
computeRnrm = false;
- DoubleHyBR(HyBRInnerSolver, HyBRRegularizationMethod, double, double, boolean, int, double, boolean) -
Constructor for class cern.colt.matrix.tdouble.algo.solver.DoubleHyBR
- Creates new instance of HyBR solver.
- DoubleIAxis - Interface in hep.aida.tdouble
- An IAxis represents a binned histogram axis.
- DoubleICC - Class in cern.colt.matrix.tdouble.algo.solver.preconditioner
- Incomplete Cholesky preconditioner without fill-in using a compressed row
matrix as internal storage
- DoubleICC(int) -
Constructor for class cern.colt.matrix.tdouble.algo.solver.preconditioner.DoubleICC
- Sets up the ICC preconditioner
- DoubleIdentity - Class in cern.colt.matrix.tdouble.algo.solver.preconditioner
-
- DoubleIdentity() -
Constructor for class cern.colt.matrix.tdouble.algo.solver.preconditioner.DoubleIdentity
-
- DoubleIHistogram - Interface in hep.aida.tdouble
- A common base interface for IHistogram1D, IHistogram2D and IHistogram3D.
- DoubleIHistogram1D - Interface in hep.aida.tdouble
- A Java interface corresponding to the AIDA 1D Histogram.
- DoubleIHistogram2D - Interface in hep.aida.tdouble
- A Java interface corresponding to the AIDA 2D Histogram.
- DoubleIHistogram3D - Interface in hep.aida.tdouble
- A Java interface corresponding to the AIDA 3D Histogram.
- DoubleILU - Class in cern.colt.matrix.tdouble.algo.solver.preconditioner
- ILU(0) preconditioner using a compressed row matrix as internal storage
- DoubleILU(int) -
Constructor for class cern.colt.matrix.tdouble.algo.solver.preconditioner.DoubleILU
- Sets up the ILU preconditioner
- DoubleILUT - Class in cern.colt.matrix.tdouble.algo.solver.preconditioner
- ILU preconditioner with fill-in.
- DoubleILUT(int, double, int) -
Constructor for class cern.colt.matrix.tdouble.algo.solver.preconditioner.DoubleILUT
- Sets up the preconditioner for the problem size
- DoubleILUT(int) -
Constructor for class cern.colt.matrix.tdouble.algo.solver.preconditioner.DoubleILUT
- Sets up the preconditioner for the given problem size.
- DoubleIntProcedure - Interface in cern.colt.function
- Interface that represents a procedure object: a procedure that takes
two arguments and does not return a value.
- DoubleIntProcedure - Interface in cern.colt.function.tdouble
- Interface that represents a procedure object: a procedure that takes two
arguments and does not return a value.
- DoubleIR - Class in cern.colt.matrix.tdouble.algo.solver
- Iterative Refinement.
- DoubleIR(DoubleMatrix1D) -
Constructor for class cern.colt.matrix.tdouble.algo.solver.DoubleIR
- Constructor for IR.
- DoubleIterationMonitor - Interface in cern.colt.matrix.tdouble.algo.solver
- Monitors the iterative solution process for convergence and divergence.
- DoubleIterationReporter - Interface in cern.colt.matrix.tdouble.algo.solver
- Reports on the progress of an iterative solver
- DoubleIterativeSolver - Interface in cern.colt.matrix.tdouble.algo.solver
- Iterative linear solver.
- DoubleListAdapter - Class in cern.colt.list.adapter
- Adapter that permits an
AbstractDoubleList
to be viewed and treated as a JDK 1.2 AbstractList
. - DoubleListAdapter(AbstractDoubleList) -
Constructor for class cern.colt.list.adapter.DoubleListAdapter
- Constructs a list backed by the specified content list.
- DoubleListAdapter - Class in cern.colt.list.tdouble
- Adapter that permits an
AbstractDoubleList
to
be viewed and treated as a JDK 1.2 AbstractList
. - DoubleListAdapter(AbstractDoubleList) -
Constructor for class cern.colt.list.tdouble.DoubleListAdapter
- Constructs a list backed by the specified content list.
- DoubleLongProcedure - Interface in cern.colt.function.tdouble
- Interface that represents a procedure object: a procedure that takes two
arguments and does not return a value.
- DoubleMatrix1D - Class in cern.colt.matrix
- Abstract base class for 1-d matrices (aka vectors) holding double elements.
- DoubleMatrix1D - Class in cern.colt.matrix.tdouble
- Abstract base class for 1-d matrices (aka vectors) holding
double elements.
- DoubleMatrix1DComparator - Interface in cern.colt.matrix.doublealgo
- A comparison function which imposes a total ordering on some
collection of elements.
- DoubleMatrix1DComparator - Interface in cern.colt.matrix.tdouble.algo
- A comparison function which imposes a total ordering on some
collection of elements.
- DoubleMatrix1DProcedure - Interface in cern.colt.matrix
- Interface that represents a condition or procedure object: takes
a single argument and returns a boolean value.
- DoubleMatrix1DProcedure - Interface in cern.colt.matrix.tdouble
- Interface that represents a condition or procedure object: takes a single
argument and returns a boolean value.
- DoubleMatrix2D - Class in cern.colt.matrix
- Abstract base class for 2-d matrices holding double elements.
- DoubleMatrix2D - Class in cern.colt.matrix.tdouble
- Abstract base class for 2-d matrices holding double elements.
- DoubleMatrix2DComparator - Interface in cern.colt.matrix.doublealgo
- A comparison function which imposes a total ordering on some
collection of elements.
- DoubleMatrix2DComparator - Interface in cern.colt.matrix.tdouble.algo
- A comparison function which imposes a total ordering on some
collection of elements.
- DoubleMatrix2DMatrix2DFunction - Interface in cern.colt.matrix.tdouble.algo
- Interface that represents a function object: a function that takes two
arguments and returns a single value.
- DoubleMatrix2DProcedure - Interface in cern.colt.matrix
- Interface that represents a condition or procedure object: takes
a single argument and returns a boolean value.
- DoubleMatrix2DProcedure - Interface in cern.colt.matrix.tdouble
- Interface that represents a condition or procedure object: takes a single
argument and returns a boolean value.
- DoubleMatrix3D - Class in cern.colt.matrix
- Abstract base class for 3-d matrices holding double elements.
- DoubleMatrix3D - Class in cern.colt.matrix.tdouble
- Abstract base class for 3-d matrices holding double elements.
- DoubleMatrix3DProcedure - Interface in cern.colt.matrix
- Interface that represents a condition or procedure object: takes
a single argument and returns a boolean value.
- DoubleMatrix3DProcedure - Interface in cern.colt.matrix.tdouble
- Interface that represents a condition or procedure object: takes a single
argument and returns a boolean value.
- DoubleMersenneTwister - Class in cern.jet.random.tdouble.engine
- MersenneTwister (MT19937) is one of the strongest uniform pseudo-random
number generators known so far; at the same time it is quick.
- DoubleMersenneTwister() -
Constructor for class cern.jet.random.tdouble.engine.DoubleMersenneTwister
- Constructs and returns a random number generator with a default seed,
which is a constant.
- DoubleMersenneTwister(int) -
Constructor for class cern.jet.random.tdouble.engine.DoubleMersenneTwister
- Constructs and returns a random number generator with the given seed.
- DoubleMersenneTwister(Date) -
Constructor for class cern.jet.random.tdouble.engine.DoubleMersenneTwister
- Constructs and returns a random number generator seeded with the given
date.
- DoubleMRNSD - Class in cern.colt.matrix.tdouble.algo.solver
- MRNSD is Modified Residual Norm Steepest Descent method used for solving
large-scale, ill-posed inverse problems of the form: b = A*x + noise.
- DoubleMRNSD() -
Constructor for class cern.colt.matrix.tdouble.algo.solver.DoubleMRNSD
-
- DoubleMult - Class in cern.jet.math.tdouble
- Only for performance tuning of compute intensive linear algebraic
computations.
- DoubleNotConvergedException - Exception in cern.colt.matrix.tdouble.algo.solver
- Signals lack of convergence of an iterative process
- DoubleNotConvergedException(DoubleNotConvergedException.Reason, String) -
Constructor for exception cern.colt.matrix.tdouble.algo.solver.DoubleNotConvergedException
- Constructor for NotConvergedException
- DoubleNotConvergedException(DoubleNotConvergedException.Reason) -
Constructor for exception cern.colt.matrix.tdouble.algo.solver.DoubleNotConvergedException
- Constructor for NotConvergedException.
- DoubleNotConvergedException.Reason - Enum in cern.colt.matrix.tdouble.algo.solver
- Possible reasons for lack of convergence
- DoublePartitioning - Class in cern.colt.matrix.tdouble.algo
- Given some interval boundaries, partitions matrices such that cell values
falling into an interval are placed next to each other.
- DoublePlusMultFirst - Class in cern.jet.math.tdouble
- Only for performance tuning of compute intensive linear algebraic
computations.
- DoublePlusMultSecond - Class in cern.jet.math.tdouble
- Only for performance tuning of compute intensive linear algebraic
computations.
- DoublePreconditioner - Interface in cern.colt.matrix.tdouble.algo.solver.preconditioner
- Preconditioner interface.
- DoubleProcedure - Interface in cern.colt.function
- Interface that represents a procedure object: a procedure that takes
a single argument and does not return a value.
- DoubleProcedure - Interface in cern.colt.function.tdouble
- Interface that represents a procedure object: a procedure that takes a single
argument and does not return a value.
- DoubleProperty - Class in cern.colt.matrix.tdouble.algo
- Tests matrices for linear algebraic properties (equality, tridiagonality,
symmetry, singularity, etc).
- DoubleProperty(double) -
Constructor for class cern.colt.matrix.tdouble.algo.DoubleProperty
- Constructs an instance with a tolerance of
Math.abs(newTolerance).
- DoubleQMR - Class in cern.colt.matrix.tdouble.algo.solver
- Quasi-Minimal Residual method.
- DoubleQMR(DoubleMatrix1D) -
Constructor for class cern.colt.matrix.tdouble.algo.solver.DoubleQMR
- Constructor for QMR.
- DoubleQMR(DoubleMatrix1D, DoublePreconditioner, DoublePreconditioner) -
Constructor for class cern.colt.matrix.tdouble.algo.solver.DoubleQMR
- Constructor for QMR.
- DoubleQuantileFinder - Interface in cern.jet.stat.quantile
- The interface shared by all quantile finders, no matter if they are exact or approximate.
- DoubleQuantileFinder - Interface in cern.jet.stat.tdouble.quantile
- The interface shared by all quantile finders, no matter if they are exact or
approximate.
- DoubleQuantileFinderFactory - Class in cern.jet.stat.tdouble.quantile
- Factory constructing exact and approximate quantile finders for both known
and unknown N.
- DoubleRandomEngine - Class in cern.jet.random.tdouble.engine
- Abstract base class for uniform pseudo-random number generating engines.
- DoubleRandomSampler - Class in cern.jet.random.tdouble.sampling
- Space and time efficiently computes a sorted Simple Random Sample Without
Replacement (SRSWOR), that is, a sorted set of n random numbers
from an interval of N numbers; Example: Computing n=3
random numbers from the interval [1,50] may yield the sorted random
set (7,13,47).
- DoubleRandomSampler(long, long, long, DoubleRandomEngine) -
Constructor for class cern.jet.random.tdouble.sampling.DoubleRandomSampler
- Constructs a random sampler that computes and delivers sorted random sets
in blocks.
- DoubleRandomSamplingAssistant - Class in cern.jet.random.tdouble.sampling
- Conveniently computes a stable Simple Random Sample Without Replacement
(SRSWOR) subsequence of n elements from a given input sequence
of N elements; Example: Computing a sublist of n=3 random
elements from a list (1,...,50) may yield the sublist
(7,13,47).
- DoubleRandomSamplingAssistant(long, long, DoubleRandomEngine) -
Constructor for class cern.jet.random.tdouble.sampling.DoubleRandomSamplingAssistant
- Constructs a random sampler that samples n random elements from
an input sequence of N elements.
- DoubleSorting - Class in cern.colt.matrix.tdouble.algo
- Matrix quicksorts and mergesorts.
- DoubleSSOR - Class in cern.colt.matrix.tdouble.algo.solver.preconditioner
- SSOR preconditioner.
- DoubleSSOR(int, boolean, double, double) -
Constructor for class cern.colt.matrix.tdouble.algo.solver.preconditioner.DoubleSSOR
- Constructor for SSOR
- DoubleSSOR(int) -
Constructor for class cern.colt.matrix.tdouble.algo.solver.preconditioner.DoubleSSOR
- Constructor for SSOR.
- DoubleStatistic - Class in cern.colt.matrix.tdouble.algo
- Basic statistics operations on matrices.
- DoubleStatistic.VectorVectorFunction - Interface in cern.colt.matrix.tdouble.algo
- Interface that represents a function object: a function that takes two
argument vectors and returns a single value.
- DoubleStencil - Class in cern.colt.matrix.tdouble.algo
- Stencil operations.
- doubleTOint(double[]) -
Static method in class flanagan.math.Fmath
-
- DoubleUniform - Class in cern.jet.random.tdouble
- Uniform distribution; Math definition and
animated definition.
- DoubleUniform(double, double, int) -
Constructor for class cern.jet.random.tdouble.DoubleUniform
- Constructs a uniform distribution with the given minimum and maximum,
using a
DoubleMersenneTwister
seeded with the given seed.
- DoubleUniform(double, double, DoubleRandomEngine) -
Constructor for class cern.jet.random.tdouble.DoubleUniform
- Constructs a uniform distribution with the given minimum and maximum.
- DoubleUniform(DoubleRandomEngine) -
Constructor for class cern.jet.random.tdouble.DoubleUniform
- Constructs a uniform distribution with min=0.0 and
max=1.0.
- doubleValue() -
Method in class org.apache.commons.math.fraction.BigFraction
-
Gets the fraction as a double.
- doubleValue() -
Method in class org.apache.commons.math.fraction.Fraction
- Gets the fraction as a double.
- doubleValue() -
Method in class org.apache.commons.math.util.BigReal
- Get the double value corresponding to the instance.
- DoubleVariableAxis - Class in hep.aida.tdouble.ref
- Variable-width axis; A reference implementation of hep.aida.IAxis.
- DoubleVariableAxis(double[]) -
Constructor for class hep.aida.tdouble.ref.DoubleVariableAxis
- Constructs and returns an axis with the given bin edges.
- DoublyLinked - Class in umontreal.iro.lecuyer.simevents.eventlist
- An implementation of
EventList
using a doubly linked linear list. - DoublyLinked() -
Constructor for class umontreal.iro.lecuyer.simevents.eventlist.DoublyLinked
-
- DOWNSIDE_VARIANCE -
Static variable in class org.apache.commons.math.stat.descriptive.moment.SemiVariance
- The DOWNSIDE Direction is used to specify that the observations below
the cutoff point will be used to calculate SemiVariance
- dpbcon(String, int, int, double[], int, double, doubleW, double[], int[], intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dpbequ(String, int, int, double[], int, double[], doubleW, doubleW, intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dpbrfs(String, int, int, int, double[], int, double[], int, double[], int, double[], int, double[], double[], double[], int[], intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dpbstf(String, int, int, double[], int, intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dpbsv(String, int, int, int, double[], int, double[], int, intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dpbsvx(String, String, int, int, int, double[], int, double[], int, StringW, double[], double[], int, double[], int, doubleW, double[], double[], double[], int[], intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dpbtf2(String, int, int, double[], int, intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dpbtrf(String, int, int, double[], int, intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dpbtrs(String, int, int, int, double[], int, double[], int, intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dpocon(String, int, double[], int, double, doubleW, double[], int[], intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dpoequ(int, double[], int, double[], doubleW, doubleW, intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dporfs(String, int, int, double[], int, double[], int, double[], int, double[], int, double[], double[], double[], int[], intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dposv(String, int, int, double[], int, double[], int, intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dposvx(String, String, int, int, double[], int, double[], int, StringW, double[], double[], int, double[], int, doubleW, double[], double[], double[], int[], intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dpotf2(String, int, double[], int, intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dpotrf(String, int, double[], int, intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dpotri(String, int, double[], int, intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dpotrs(String, int, int, double[], int, double[], int, intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dppcon(String, int, double[], double, doubleW, double[], int[], intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dppequ(String, int, double[], double[], doubleW, doubleW, intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dpprfs(String, int, int, double[], double[], double[], int, double[], int, double[], double[], double[], int[], intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dppsv(String, int, int, double[], double[], int, intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dppsvx(String, String, int, int, double[], double[], StringW, double[], double[], int, double[], int, doubleW, double[], double[], double[], int[], intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dpptrf(String, int, double[], intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dpptri(String, int, double[], intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dpptrs(String, int, int, double[], double[], int, intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dptcon(int, double[], double[], double, doubleW, double[], intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dpteqr(String, int, double[], double[], double[], int, double[], intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dptrfs(int, int, double[], double[], double[], double[], double[], int, double[], int, double[], double[], double[], intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dptsv(int, int, double[], double[], double[], int, intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dptsvx(String, int, int, double[], double[], double[], double[], double[], int, double[], int, doubleW, double[], double[], double[], intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dpttrf(int, double[], double[], intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dpttrs(int, int, double[], double[], double[], int, intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dptts2(int, int, double[], double[], double[], int) -
Method in class org.netlib.lapack.LAPACK
-
..
- DRand - Class in cern.jet.random.engine
- Quick medium quality uniform pseudo-random number generator.
- DRand() -
Constructor for class cern.jet.random.engine.DRand
- Constructs and returns a random number generator with a default seed, which is a constant.
- DRand(int) -
Constructor for class cern.jet.random.engine.DRand
- Constructs and returns a random number generator with the given seed.
- DRand(Date) -
Constructor for class cern.jet.random.engine.DRand
- Constructs and returns a random number generator seeded with the given date.
- DRand - Class in cern.jet.random.tdouble.engine
- Quick medium quality uniform pseudo-random number generator.
- DRand() -
Constructor for class cern.jet.random.tdouble.engine.DRand
- Constructs and returns a random number generator with a default seed,
which is a constant.
- DRand(int) -
Constructor for class cern.jet.random.tdouble.engine.DRand
- Constructs and returns a random number generator with the given seed.
- DRand(Date) -
Constructor for class cern.jet.random.tdouble.engine.DRand
- Constructs and returns a random number generator seeded with the given
date.
- draw(P1D) -
Method in class jhplot.HChart
- Draw data from a P1D.
- draw(HLabel) -
Method in class jhplot.HPlot
- Draw a label.
- draw(HKey) -
Method in class jhplot.HPlot
- Draw a key.
- draw(HLabelEq) -
Method in class jhplot.HPlot
- Draw a LaTeX rquation on the Canvas.
- draw(HShape) -
Method in class jhplot.HPlot
- Draw a shape primitive to the Canvas.
- draw(HMLabel) -
Method in class jhplot.HPlot
- Draw a multiline label.
- draw(H1D[]) -
Method in class jhplot.HPlot
- Draw array of histograms
- draw(Cloud1D) -
Method in class jhplot.HPlot
- Plot cloud in 1D.
- draw(DataPointSet) -
Method in class jhplot.HPlot
- Plot Aida datapointset.
- draw(Cloud2D) -
Method in class jhplot.HPlot
- Plot cloud 2D
- draw(Histogram1D) -
Method in class jhplot.HPlot
- Draw 1D histogram
- draw(H1D) -
Method in class jhplot.HPlot
- Plot 1D histogram.
- draw(F1D[]) -
Method in class jhplot.HPlot
- Draw array of F1D holders
- draw(DataArray, int) -
Method in class jhplot.HPlot
- Draw input data represented by DataArray
- draw(F1D) -
Method in class jhplot.HPlot
- Draw an one-dimensional function.
- draw(FND) -
Method in class jhplot.HPlot
- Draw an one-dimensional function from FND
- draw(F1D, boolean) -
Method in class jhplot.HPlot
- Draw an one-dimensional function.
- draw(FND, boolean) -
Method in class jhplot.HPlot
- Draw an one-dimensional function from FND.
- draw(P1D[]) -
Method in class jhplot.HPlot
- Draw array of P1D holders
- draw(P1D) -
Method in class jhplot.HPlot
- Draw data in form of P1D
- draw(Cloud2D) -
Method in class jhplot.HPlot2D
- Plot cloud 2D.
- draw(Histogram2D) -
Method in class jhplot.HPlot2D
- Draw 2D histogram
- draw(H2D) -
Method in class jhplot.HPlot2D
- Draw 2D histogram using a style (see setStyle())
- draw(P1D) -
Method in class jhplot.HPlot2D
- Plot P1D data (x-y) as density plot
- draw(F2D) -
Method in class jhplot.HPlot2D
- Plot F2D function (x-y) as density plot
- draw(H2D) -
Method in class jhplot.HPlot3D
- Draw H2D histogram
- draw(P2D) -
Method in class jhplot.HPlot3D
- Display P2D data holder with X,Y,Z values in 3D.
- draw(P3D) -
Method in class jhplot.HPlot3D
- Display P3D data holder with X,Y,Z values in 3D as surface.
- draw(H2D, H2D) -
Method in class jhplot.HPlot3D
- Plot two H2D histograms on the same plot.
- draw(F2D) -
Method in class jhplot.HPlot3D
- Draw F2D function as a surface.
- draw(F2D, F2D) -
Method in class jhplot.HPlot3D
- Draw two F2D functions on the same plot.
- draw(H2D, F2D) -
Method in class jhplot.HPlot3D
- Draw H2D histogram and F2D function on the same plot.
- draw(F2D, H2D) -
Method in class jhplot.HPlot3D
- Draw F2D and H2D on the same plot.
- draw(FPR) -
Method in class jhplot.HPlot3DP
- Draw a parametric function
- draw(H1D, int, int) -
Method in class jhplot.HPlotJa
- Draw H1D histogram on pad X and pad Y
- draw(H2D, int, int) -
Method in class jhplot.HPlotJa
- Draw 2D histogram on pads given by X and Y.
- draw(JaObject) -
Method in class jhplot.HPlotJa
- Draw JaObject.
- draw(P1D) -
Method in class jhplot.HPlotJa
- Draw H2D histogram on the current pad.
- draw(H2D) -
Method in class jhplot.HPlotJa
- Draw H2D histogram on the current pad.
- draw(H1D) -
Method in class jhplot.HPlotJa
- Draw H1D histogram on the current pad.
- draw(F1D[]) -
Method in class jhplot.HPlotJa
- Draw array of F1D holders
- draw(Cloud1D) -
Method in class jhplot.HPlotJa
- Plot cloud in 1D.
- draw(Cloud2D) -
Method in class jhplot.HPlotJa
- Plot cloud 2D
- draw(Histogram1D) -
Method in class jhplot.HPlotJa
- Draw 1D histogram
- draw(DataArray, String) -
Method in class jhplot.HPlotJa
- Draw data represented by DataArray on the current pad.
- draw(F1D, int, int) -
Method in class jhplot.HPlotJa
- Draw an one-dimensional function on the current pad.
- draw(FND, int, int) -
Method in class jhplot.HPlotJa
- Draw an one-dimensional function on the current pad.
- draw(F1D) -
Method in class jhplot.HPlotJa
- Draw an one-dimensional function on the current pad.
- draw(FND) -
Method in class jhplot.HPlotJa
- Draw an one-dimensional function on the current pad.
- draw(P1D, int, int) -
Method in class jhplot.HPlotJa
- Draw P1D object on the pad
- draw(P1D[]) -
Method in class jhplot.HPlotJa
- Draw array of P1D holders
- draw(Object3d) -
Method in class jhplot.HView3D
- Draw an object.
- draw(ConstructionObject) -
Method in class jhplot.HZirkel
- Draw an object on the canvas.
- draw(double[][], double[][]) -
Method in class jhplot.SPlot
- Draw multiple sets as marks (default).
- draw(double[], double[]) -
Method in class jhplot.SPlot
- Draw a single data set as marks (default).
- draw(String, double[], double[]) -
Method in class jhplot.SPlot
- Draw a single data set with a legend.
- draw(String, double[], double[], double[]) -
Method in class jhplot.SPlot
- Draw a single data set with errors on Y with legend.
- draw(H1D) -
Method in class jhplot.SPlot
- Draw H1D histograms
- draw(P1D) -
Method in class jhplot.SPlot
- Draw P1D object.
- draw(String[], double[][], double[][]) -
Method in class jhplot.SPlot
- Set sets of data with legends
- drawBox() -
Method in class jhplot.HPlot3D
- Draw an empty frame
- drawCdf(ContinuousDistribution, double, double, int, String) -
Static method in class umontreal.iro.lecuyer.gof.GofFormat
- Formats data to plot the graph of the distribution function F over the
interval [a, b], and returns the result as a
String
.
- drawData(VectorGraphics) -
Method in class jhplot.jadraw.JaAxes
- Draw data points
- drawDensity(ContinuousDistribution, double, double, int, String) -
Static method in class umontreal.iro.lecuyer.gof.GofFormat
- Formats data to plot the graph of the density f (x) over the interval [a, b],
and returns the result as a
String
.
- drawHandles(VectorGraphics) -
Method in class jhplot.jadraw.JaArcObject
- Draws the handles of this JaxoArc.
- drawHandles(VectorGraphics) -
Method in class jhplot.jadraw.JaAxes
- Draws the handles of this box object.
- drawHandles(VectorGraphics) -
Method in class jhplot.jadraw.JaBlob
- Draws a visual aid during the dragging of a blob object,
which is a red cross at the center.
- drawHandles(VectorGraphics) -
Method in class jhplot.jadraw.JaBox
- Draws the handles of this box object.
- drawHandles(VectorGraphics) -
Method in class jhplot.jadraw.JaKey
- Draws the handles of this text object.
- drawHandles(VectorGraphics) -
Method in class jhplot.jadraw.JaLatexText
- Draws the handles of this text object.
- drawHandles(VectorGraphics) -
Method in class jhplot.jadraw.JaLineObject
- Draws the handles of this line object.
- drawHandles(VectorGraphics) -
Method in class jhplot.jadraw.JaLoopObject
- Draws the handles of this loop object.
- drawHandles(VectorGraphics) -
Method in class jhplot.jadraw.JaObject
- Draws the handles of this JaObject that allow
to move/resize/edit it.
- drawHandles(VectorGraphics) -
Method in class jhplot.jadraw.JaText
- Draws the handles of this text object.
- drawHandles(VectorGraphics) -
Method in class jhplot.jadraw.JaTextBox
- Draws the handles of this box object.
- drawHandles(VectorGraphics) -
Method in class jhplot.jadraw.JaVertex
- Draws the handles of this vertex object.
- drawHandles(VectorGraphics) -
Method in class jhplot.jadraw.JaVertexT5
- Draws the handles of this vertex object.
- drawItem(Graphics2D, XYItemRendererState, Rectangle2D, PlotRenderingInfo, XYPlot, ValueAxis, ValueAxis, XYDataset, int, int, CrosshairState, int) -
Method in class umontreal.iro.lecuyer.charts.EmpiricalRenderer
- Draws the visual representation of a single data item.
- DrawOptions - Class in jhplot
- Main class which sets graphic attributes for all jHPlot classes (histograms
and data holders).
- DrawOptions() -
Constructor for class jhplot.DrawOptions
- Sets drawing options
- drawStatBox(H1D) -
Method in class jhplot.HPlot
- Draw a statistical box (mean, RMS, number of entries)
- drawStatBox(H1D, int, int) -
Method in class jhplot.HPlot
- Draw a statistical box (mean, RMS, number of entries) at a specific position.
- drawTextBox(String[]) -
Method in class jhplot.HPlot
- Draw a text box with some information
- drawTexVisualAid(VectorGraphics) -
Method in class jhplot.jadraw.JaLatexText
- Draws a visual aid for a tex label:
a blu TeX icon.
- drawVisualAid(VectorGraphics) -
Method in class jhplot.jadraw.JaArcObject
- Draws a visual aid during the dragging of an arc object.
- drawVisualAid(VectorGraphics) -
Method in class jhplot.jadraw.JaBlob
- Draws a visual aid during the dragging of a blob object,
which is a red cross at the center.
- drawVisualAid(VectorGraphics) -
Method in class jhplot.jadraw.JaLoopObject
- Draws a visual aid during the dragging of a loop object,
which is a red cross at the center.
- drawVisualAid(VectorGraphics) -
Method in class jhplot.jadraw.JaObject
- Draws a visual aid for the user during dragging of certain JaxoObjects.
- drawVisualAid(VectorGraphics) -
Method in class jhplot.jadraw.JaVertex
- Draws a visual aid during the dragging of a vertex object,
which is a red cross at the center.
- drawVisualAid(VectorGraphics) -
Method in class jhplot.jadraw.JaVertexT5
- Draws a visual aid during the dragging of a vertex object,
which is a red cross at the center.
- drot(DoubleMatrix1D, DoubleMatrix1D, double, double) -
Method in interface cern.colt.matrix.linalg.Blas
- Applies a givens plane rotation to (x,y); x = c*x + s*y; y = c*y - s*x.
- drot(DoubleMatrix1D, DoubleMatrix1D, double, double) -
Method in class cern.colt.matrix.linalg.SeqBlas
-
- drot(DoubleMatrix1D, DoubleMatrix1D, double, double) -
Method in class cern.colt.matrix.linalg.SmpBlas
-
- drot(DoubleMatrix1D, DoubleMatrix1D, double, double) -
Method in interface cern.colt.matrix.tdouble.algo.DoubleBlas
- Applies a givens plane rotation to (x,y);
x = c*x + s*y; y = c*y - s*x.
- drot(DoubleMatrix1D, DoubleMatrix1D, double, double) -
Method in class cern.colt.matrix.tdouble.algo.SmpDoubleBlas
-
- drot(FloatMatrix1D, FloatMatrix1D, float, float) -
Method in interface cern.colt.matrix.tfloat.algo.FloatBlas
- Applies a givens plane rotation to (x,y);
x = c*x + s*y; y = c*y - s*x.
- drot(FloatMatrix1D, FloatMatrix1D, float, float) -
Method in class cern.colt.matrix.tfloat.algo.SmpFloatBlas
-
- drot(int, double[], int, double[], int, double, double) -
Method in class org.netlib.blas.BLAS
-
..
- drotg(double, double, double[]) -
Method in interface cern.colt.matrix.linalg.Blas
- Constructs a Givens plane rotation for (a,b).
- drotg(double, double, double[]) -
Method in class cern.colt.matrix.linalg.SeqBlas
-
- drotg(double, double, double[]) -
Method in class cern.colt.matrix.linalg.SmpBlas
-
- drotg(double, double, double[]) -
Method in interface cern.colt.matrix.tdouble.algo.DoubleBlas
- Constructs a Givens plane rotation for (a,b).
- drotg(double, double, double[]) -
Method in class cern.colt.matrix.tdouble.algo.SmpDoubleBlas
-
- drotg(float, float, float[]) -
Method in interface cern.colt.matrix.tfloat.algo.FloatBlas
- Constructs a Givens plane rotation for (a,b).
- drotg(float, float, float[]) -
Method in class cern.colt.matrix.tfloat.algo.SmpFloatBlas
-
- drotg(doubleW, doubleW, doubleW, doubleW) -
Method in class org.netlib.blas.BLAS
-
..
- drotm(int, double[], int, double[], int, double[]) -
Method in class org.netlib.blas.BLAS
-
..
- drotmg(doubleW, doubleW, doubleW, double, double[]) -
Method in class org.netlib.blas.BLAS
-
..
- drscl(int, double, double[], int) -
Method in class org.netlib.lapack.LAPACK
-
..
- dsaitr(intW, String, int, int, int, int, double[], doubleW, double[], int, double[], int, int[], double[], intW) -
Method in class org.netlib.arpack.ARPACK
- No documentation was available when generating this method.
- dsapps(int, int, int, double[], double[], int, double[], int, double[], double[], int, double[]) -
Method in class org.netlib.arpack.ARPACK
- No documentation was available when generating this method.
- dsaup2(intW, String, int, String, intW, intW, double, double[], int, int, int, intW, double[], int, double[], int, double[], double[], double[], int, double[], int[], double[], intW) -
Method in class org.netlib.arpack.ARPACK
- No documentation was available when generating this method.
- dsaupd(intW, String, int, String, int, doubleW, double[], int, double[], int, int[], int[], double[], double[], int, intW) -
Method in class org.netlib.arpack.ARPACK
- No documentation was available when generating this method.
- dsbev(String, String, int, int, double[], int, double[], double[], int, double[], intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dsbevd(String, String, int, int, double[], int, double[], double[], int, double[], int, int[], int, intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dsbevx(String, String, String, int, int, double[], int, double[], int, double, double, int, int, double, intW, double[], double[], int, double[], int[], int[], intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dsbgst(String, String, int, int, int, double[], int, double[], int, double[], int, double[], intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dsbgv(String, String, int, int, int, double[], int, double[], int, double[], double[], int, double[], intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dsbgvd(String, String, int, int, int, double[], int, double[], int, double[], double[], int, double[], int, int[], int, intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dsbgvx(String, String, String, int, int, int, double[], int, double[], int, double[], int, double, double, int, int, double, intW, double[], double[], int, double[], int[], int[], intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dsbmv(String, int, int, double, double[], int, double[], int, double, double[], int) -
Method in class org.netlib.blas.BLAS
-
..
- dsbtrd(String, String, int, int, double[], int, double[], double[], double[], int, double[], intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dscal(double, DoubleMatrix1D) -
Method in interface cern.colt.matrix.linalg.Blas
- Vector scaling; x = alpha*x.
- dscal(double, DoubleMatrix2D) -
Method in interface cern.colt.matrix.linalg.Blas
- Matrix scaling; A = alpha*A.
- dscal(double, DoubleMatrix1D) -
Method in class cern.colt.matrix.linalg.SeqBlas
-
- dscal(double, DoubleMatrix2D) -
Method in class cern.colt.matrix.linalg.SeqBlas
-
- dscal(double, DoubleMatrix1D) -
Method in class cern.colt.matrix.linalg.SmpBlas
-
- dscal(double, DoubleMatrix2D) -
Method in class cern.colt.matrix.linalg.SmpBlas
-
- dscal(double, DoubleMatrix1D) -
Method in interface cern.colt.matrix.tdouble.algo.DoubleBlas
- Vector scaling; x = alpha*x.
- dscal(double, DoubleMatrix2D) -
Method in interface cern.colt.matrix.tdouble.algo.DoubleBlas
- Matrix scaling; A = alpha*A.
- dscal(double, DoubleMatrix1D) -
Method in class cern.colt.matrix.tdouble.algo.SmpDoubleBlas
-
- dscal(double, DoubleMatrix2D) -
Method in class cern.colt.matrix.tdouble.algo.SmpDoubleBlas
-
- dscal(float, FloatMatrix1D) -
Method in interface cern.colt.matrix.tfloat.algo.FloatBlas
- Vector scaling; x = alpha*x.
- dscal(float, FloatMatrix2D) -
Method in interface cern.colt.matrix.tfloat.algo.FloatBlas
- Matrix scaling; A = alpha*A.
- dscal(float, FloatMatrix1D) -
Method in class cern.colt.matrix.tfloat.algo.SmpFloatBlas
-
- dscal(float, FloatMatrix2D) -
Method in class cern.colt.matrix.tfloat.algo.SmpFloatBlas
-
- dscal(int, double, double[], int) -
Method in class org.netlib.blas.BLAS
-
..
- dsconv(int, double[], double[], double, intW) -
Method in class org.netlib.arpack.ARPACK
- No documentation was available when generating this method.
- dsecnd() -
Method in class org.netlib.lapack.LAPACK
-
-- LAPACK auxiliary routine (version 3.1.1) --
Univ.
- dseigt(double, int, double[], int, double[], double[], double[], intW) -
Method in class org.netlib.arpack.ARPACK
- No documentation was available when generating this method.
- dsesrt(String, boolean, int, double[], int, double[], int) -
Method in class org.netlib.arpack.ARPACK
- No documentation was available when generating this method.
- dseupd(boolean, String, boolean[], double[], double[], int, double, String, int, String, intW, double, double[], int, double[], int, int[], int[], double[], double[], int, intW) -
Method in class org.netlib.arpack.ARPACK
- No documentation was available when generating this method.
- dsgesv(int, int, double[], int, int[], double[], int, double[], int, double[], float[], intW, intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dsgets(int, String, intW, intW, double[], double[], double[]) -
Method in class org.netlib.arpack.ARPACK
- No documentation was available when generating this method.
- DSOLProcessSimulator - Class in umontreal.iro.lecuyer.simprocs
- Represents a simulation process whose actions method is
interpreted by the DSOL interpreter, written by
Peter Jacobs (http://www.tbm.tudelft.nl/webstaf/peterja/index.htm).
- DSOLProcessSimulator() -
Constructor for class umontreal.iro.lecuyer.simprocs.DSOLProcessSimulator
- Constructs a new DSOLProcessSimulator variable without initialization.
- dsortc(String, boolean, int, double[], double[], double[]) -
Method in class org.netlib.arpack.ARPACK
- No documentation was available when generating this method.
- dsortr(String, boolean, int, double[], double[]) -
Method in class org.netlib.arpack.ARPACK
- No documentation was available when generating this method.
- dspcon(String, int, double[], int[], double, doubleW, double[], int[], intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dspev(String, String, int, double[], double[], double[], int, double[], intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dspevd(String, String, int, double[], double[], double[], int, double[], int, int[], int, intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dspevx(String, String, String, int, double[], double, double, int, int, double, intW, double[], double[], int, double[], int[], int[], intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dspgst(int, String, int, double[], double[], intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dspgv(int, String, String, int, double[], double[], double[], double[], int, double[], intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dspgvd(int, String, String, int, double[], double[], double[], double[], int, double[], int, int[], int, intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dspgvx(int, String, String, String, int, double[], double[], double, double, int, int, double, intW, double[], double[], int, double[], int[], int[], intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dspmv(String, int, double, double[], double[], int, double, double[], int) -
Method in class org.netlib.blas.BLAS
-
..
- dspr(String, int, double, double[], int, double[]) -
Method in class org.netlib.blas.BLAS
-
..
- dspr2(String, int, double, double[], int, double[], int, double[]) -
Method in class org.netlib.blas.BLAS
-
..
- dsprfs(String, int, int, double[], double[], int[], double[], int, double[], int, double[], double[], double[], int[], intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dspsv(String, int, int, double[], int[], double[], int, intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dspsvx(String, String, int, int, double[], double[], int[], double[], int, double[], int, doubleW, double[], double[], double[], int[], intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dsptrd(String, int, double[], double[], double[], double[], intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dsptrf(String, int, double[], int[], intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dsptri(String, int, double[], int[], double[], intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dsptrs(String, int, int, double[], int[], double[], int, intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dst(boolean) -
Method in class cern.colt.matrix.tdouble.impl.DenseDoubleMatrix1D
- Computes the discrete sine transform (DST-II) of this matrix.
- dst(boolean) -
Method in class cern.colt.matrix.tfloat.impl.DenseFloatMatrix1D
- Computes the discrete sine transform (DST-II) of this matrix.
- dst2(boolean) -
Method in class cern.colt.matrix.tdouble.impl.DenseColumnDoubleMatrix2D
- Computes the 2D discrete sine transform (DST-II) of this matrix.
- dst2(boolean) -
Method in class cern.colt.matrix.tdouble.impl.DenseDoubleMatrix2D
- Computes the 2D discrete sine transform (DST-II) of this matrix.
- dst2(boolean) -
Method in class cern.colt.matrix.tdouble.impl.DenseLargeDoubleMatrix2D
- Computes the 2D discrete sine transform (DST-II) of this matrix.
- dst2(boolean) -
Method in class cern.colt.matrix.tdouble.impl.WrapperDoubleMatrix2D
- Computes the 2D discrete sine transform (DST-II) of this matrix.
- dst2(boolean) -
Method in class cern.colt.matrix.tfloat.impl.DenseColumnFloatMatrix2D
- Computes the 2D discrete sine transform (DST-II) of this matrix.
- dst2(boolean) -
Method in class cern.colt.matrix.tfloat.impl.DenseFloatMatrix2D
- Computes the 2D discrete sine transform (DST-II) of this matrix.
- dst2(boolean) -
Method in class cern.colt.matrix.tfloat.impl.DenseLargeFloatMatrix2D
- Computes the 2D discrete sine transform (DST-II) of this matrix.
- dst2(boolean) -
Method in class cern.colt.matrix.tfloat.impl.WrapperFloatMatrix2D
- Computes the 2D discrete sine transform (DST-II) of this matrix.
- dst2Slices(boolean) -
Method in class cern.colt.matrix.tdouble.impl.DenseDoubleMatrix3D
- Computes the 2D discrete sine transform (DST-II) of each slice of this
matrix.
- dst2Slices(boolean) -
Method in class cern.colt.matrix.tdouble.impl.DenseLargeDoubleMatrix3D
- Computes the 2D discrete sine transform (DST-II) of each slice of this
matrix.
- dst2Slices(boolean) -
Method in class cern.colt.matrix.tdouble.impl.WrapperDoubleMatrix3D
- Computes the 2D discrete sine transform (DST-II) of each slice of this
matrix.
- dst2Slices(boolean) -
Method in class cern.colt.matrix.tfloat.impl.DenseFloatMatrix3D
- Computes the 2D discrete sine transform (DST-II) of each slice of this
matrix.
- dst2Slices(boolean) -
Method in class cern.colt.matrix.tfloat.impl.DenseLargeFloatMatrix3D
- Computes the 2D discrete sine transform (DST-II) of each slice of this
matrix.
- dst2Slices(boolean) -
Method in class cern.colt.matrix.tfloat.impl.WrapperFloatMatrix3D
- Computes the 2D discrete sine transform (DST-II) of each slice of this
matrix.
- dst3(boolean) -
Method in class cern.colt.matrix.tdouble.impl.DenseDoubleMatrix3D
- Computes the 3D discrete sine transform (DST-II) of this matrix.
- dst3(boolean) -
Method in class cern.colt.matrix.tdouble.impl.DenseLargeDoubleMatrix3D
- Computes the 3D discrete sine transform (DST-II) of this matrix.
- dst3(boolean) -
Method in class cern.colt.matrix.tdouble.impl.WrapperDoubleMatrix3D
- Computes the 3D discrete sine transform (DST-II) of this matrix.
- dst3(boolean) -
Method in class cern.colt.matrix.tfloat.impl.DenseFloatMatrix3D
- Computes the 3D discrete sine transform (DST-II) of this matrix.
- dst3(boolean) -
Method in class cern.colt.matrix.tfloat.impl.DenseLargeFloatMatrix3D
- Computes the 3D discrete sine transform (DST-II) of this matrix.
- dst3(boolean) -
Method in class cern.colt.matrix.tfloat.impl.WrapperFloatMatrix3D
- Computes the 3D discrete sine transform (DST-II) of this matrix.
- dstatn() -
Method in class org.netlib.arpack.ARPACK
- No documentation was available when generating this method.
- dstats() -
Method in class org.netlib.arpack.ARPACK
- No documentation was available when generating this method.
- dstColumns(boolean) -
Method in class cern.colt.matrix.tdouble.impl.DenseColumnDoubleMatrix2D
- Computes the discrete sine transform (DST-II) of each column of this
matrix.
- dstColumns(boolean) -
Method in class cern.colt.matrix.tdouble.impl.DenseDoubleMatrix2D
- Computes the discrete sine transform (DST-II) of each column of this
matrix.
- dstColumns(boolean) -
Method in class cern.colt.matrix.tdouble.impl.DenseLargeDoubleMatrix2D
- Computes the discrete sine transform (DST-II) of each column of this
matrix.
- dstColumns(boolean) -
Method in class cern.colt.matrix.tdouble.impl.WrapperDoubleMatrix2D
- Computes the discrete sine transform (DST-II) of each column of this
matrix.
- dstColumns(boolean) -
Method in class cern.colt.matrix.tfloat.impl.DenseColumnFloatMatrix2D
- Computes the discrete sine transform (DST-II) of each column of this
matrix.
- dstColumns(boolean) -
Method in class cern.colt.matrix.tfloat.impl.DenseFloatMatrix2D
- Computes the discrete sine transform (DST-II) of each column of this
matrix.
- dstColumns(boolean) -
Method in class cern.colt.matrix.tfloat.impl.DenseLargeFloatMatrix2D
- Computes the discrete sine transform (DST-II) of each column of this
matrix.
- dstColumns(boolean) -
Method in class cern.colt.matrix.tfloat.impl.WrapperFloatMatrix2D
- Computes the discrete sine transform (DST-II) of each column of this
matrix.
- dstebz(String, String, int, double, double, int, int, double, double[], double[], intW, intW, double[], int[], int[], double[], int[], intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dstedc(String, int, double[], double[], double[], int, double[], int, int[], int, intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dstegr(String, String, int, double[], double[], double, double, int, int, double, intW, double[], double[], int, int[], double[], int, int[], int, intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dstein(int, double[], double[], int, double[], int[], int[], double[], int, double[], int[], int[], intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dstemr(String, String, int, double[], double[], double, double, int, int, intW, double[], double[], int, int, int[], booleanW, double[], int, int[], int, intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dsteqr(String, int, double[], double[], double[], int, double[], intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dsterf(int, double[], double[], intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dstev(String, int, double[], double[], double[], int, double[], intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dstevd(String, int, double[], double[], double[], int, double[], int, int[], int, intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dstevr(String, String, int, double[], double[], double, double, int, int, double, intW, double[], double[], int, int[], double[], int, int[], int, intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dstevx(String, String, int, double[], double[], double, double, int, int, double, intW, double[], double[], int, double[], int[], int[], intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dstqrb(int, double[], double[], double[], double[], intW) -
Method in class org.netlib.arpack.ARPACK
- No documentation was available when generating this method.
- dstRows(boolean) -
Method in class cern.colt.matrix.tdouble.impl.DenseColumnDoubleMatrix2D
- Computes the discrete sine transform (DST-II) of each row of this matrix.
- dstRows(boolean) -
Method in class cern.colt.matrix.tdouble.impl.DenseDoubleMatrix2D
- Computes the discrete sine transform (DST-II) of each row of this matrix.
- dstRows(boolean) -
Method in class cern.colt.matrix.tdouble.impl.DenseLargeDoubleMatrix2D
- Computes the discrete sine transform (DST-II) of each row of this matrix.
- dstRows(boolean) -
Method in class cern.colt.matrix.tdouble.impl.WrapperDoubleMatrix2D
- Computes the discrete sine transform (DST-II) of each row of this matrix.
- dstRows(boolean) -
Method in class cern.colt.matrix.tfloat.impl.DenseColumnFloatMatrix2D
- Computes the discrete sine transform (DST-II) of each row of this matrix.
- dstRows(boolean) -
Method in class cern.colt.matrix.tfloat.impl.DenseFloatMatrix2D
- Computes the discrete sine transform (DST-II) of each row of this matrix.
- dstRows(boolean) -
Method in class cern.colt.matrix.tfloat.impl.DenseLargeFloatMatrix2D
- Computes the discrete sine transform (DST-II) of each row of this matrix.
- dstRows(boolean) -
Method in class cern.colt.matrix.tfloat.impl.WrapperFloatMatrix2D
- Computes the discrete sine transform (DST-II) of each row of this matrix.
- dswap(DoubleMatrix1D, DoubleMatrix1D) -
Method in interface cern.colt.matrix.linalg.Blas
- Swaps the elements of two vectors; y <==> x.
- dswap(DoubleMatrix2D, DoubleMatrix2D) -
Method in interface cern.colt.matrix.linalg.Blas
- Swaps the elements of two matrices; B <==> A.
- dswap(DoubleMatrix1D, DoubleMatrix1D) -
Method in class cern.colt.matrix.linalg.SeqBlas
-
- dswap(DoubleMatrix2D, DoubleMatrix2D) -
Method in class cern.colt.matrix.linalg.SeqBlas
-
- dswap(DoubleMatrix1D, DoubleMatrix1D) -
Method in class cern.colt.matrix.linalg.SmpBlas
-
- dswap(DoubleMatrix2D, DoubleMatrix2D) -
Method in class cern.colt.matrix.linalg.SmpBlas
-
- dswap(DoubleMatrix1D, DoubleMatrix1D) -
Method in interface cern.colt.matrix.tdouble.algo.DoubleBlas
- Swaps the elements of two vectors; y <==> x.
- dswap(DoubleMatrix2D, DoubleMatrix2D) -
Method in interface cern.colt.matrix.tdouble.algo.DoubleBlas
- Swaps the elements of two matrices; B <==> A.
- dswap(DoubleMatrix1D, DoubleMatrix1D) -
Method in class cern.colt.matrix.tdouble.algo.SmpDoubleBlas
-
- dswap(DoubleMatrix2D, DoubleMatrix2D) -
Method in class cern.colt.matrix.tdouble.algo.SmpDoubleBlas
-
- dswap(FloatMatrix1D, FloatMatrix1D) -
Method in interface cern.colt.matrix.tfloat.algo.FloatBlas
- Swaps the elements of two vectors; y <==> x.
- dswap(FloatMatrix2D, FloatMatrix2D) -
Method in interface cern.colt.matrix.tfloat.algo.FloatBlas
- Swaps the elements of two matrices; B <==> A.
- dswap(FloatMatrix1D, FloatMatrix1D) -
Method in class cern.colt.matrix.tfloat.algo.SmpFloatBlas
-
- dswap(FloatMatrix2D, FloatMatrix2D) -
Method in class cern.colt.matrix.tfloat.algo.SmpFloatBlas
-
- dswap(int, double[], int, double[], int) -
Method in class org.netlib.blas.BLAS
-
..
- dsycon(String, int, double[], int, int[], double, doubleW, double[], int[], intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dsyev(String, String, int, double[], int, double[], double[], int, intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dsyevd(String, String, int, double[], int, double[], double[], int, int[], int, intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dsyevr(String, String, String, int, double[], int, double, double, int, int, double, intW, double[], double[], int, int[], double[], int, int[], int, intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dsyevx(String, String, String, int, double[], int, double, double, int, int, double, intW, double[], double[], int, double[], int, int[], int[], intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dsygs2(int, String, int, double[], int, double[], int, intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dsygst(int, String, int, double[], int, double[], int, intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dsygv(int, String, String, int, double[], int, double[], int, double[], double[], int, intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dsygvd(int, String, String, int, double[], int, double[], int, double[], double[], int, int[], int, intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dsygvx(int, String, String, String, int, double[], int, double[], int, double, double, int, int, double, intW, double[], double[], int, double[], int, int[], int[], intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dsymm(String, String, int, int, double, double[], int, double[], int, double, double[], int) -
Method in class org.netlib.blas.BLAS
-
..
- dsymv(boolean, double, DoubleMatrix2D, DoubleMatrix1D, double, DoubleMatrix1D) -
Method in interface cern.colt.matrix.linalg.Blas
- Symmetric matrix-vector multiplication; y = alpha*A*x + beta*y.
- dsymv(boolean, double, DoubleMatrix2D, DoubleMatrix1D, double, DoubleMatrix1D) -
Method in class cern.colt.matrix.linalg.SeqBlas
-
- dsymv(boolean, double, DoubleMatrix2D, DoubleMatrix1D, double, DoubleMatrix1D) -
Method in class cern.colt.matrix.linalg.SmpBlas
-
- dsymv(boolean, double, DoubleMatrix2D, DoubleMatrix1D, double, DoubleMatrix1D) -
Method in interface cern.colt.matrix.tdouble.algo.DoubleBlas
- Symmetric matrix-vector multiplication; y = alpha*A*x + beta*y.
- dsymv(boolean, double, DoubleMatrix2D, DoubleMatrix1D, double, DoubleMatrix1D) -
Method in class cern.colt.matrix.tdouble.algo.SmpDoubleBlas
-
- dsymv(boolean, float, FloatMatrix2D, FloatMatrix1D, float, FloatMatrix1D) -
Method in interface cern.colt.matrix.tfloat.algo.FloatBlas
- Symmetric matrix-vector multiplication; y = alpha*A*x + beta*y.
- dsymv(boolean, float, FloatMatrix2D, FloatMatrix1D, float, FloatMatrix1D) -
Method in class cern.colt.matrix.tfloat.algo.SmpFloatBlas
-
- dsymv(String, int, double, double[], int, double[], int, double, double[], int) -
Method in class org.netlib.blas.BLAS
-
..
- dsyr(String, int, double, double[], int, double[], int) -
Method in class org.netlib.blas.BLAS
-
..
- dsyr2(String, int, double, double[], int, double[], int, double[], int) -
Method in class org.netlib.blas.BLAS
-
..
- dsyr2k(String, String, int, int, double, double[], int, double[], int, double, double[], int) -
Method in class org.netlib.blas.BLAS
-
..
- dsyrfs(String, int, int, double[], int, double[], int, int[], double[], int, double[], int, double[], double[], double[], int[], intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dsyrk(String, String, int, int, double, double[], int, double, double[], int) -
Method in class org.netlib.blas.BLAS
-
..
- dsysv(String, int, int, double[], int, int[], double[], int, double[], int, intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dsysvx(String, String, int, int, double[], int, double[], int, int[], double[], int, double[], int, doubleW, double[], double[], double[], int, int[], intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dsytd2(String, int, double[], int, double[], double[], double[], intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dsytf2(String, int, double[], int, int[], intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dsytrd(String, int, double[], int, double[], double[], double[], double[], int, intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dsytrf(String, int, double[], int, int[], double[], int, intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dsytri(String, int, double[], int, int[], double[], intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dsytrs(String, int, int, double[], int, int[], double[], int, intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dtbcon(String, String, String, int, int, double[], int, doubleW, double[], int[], intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dtbmv(String, String, String, int, int, double[], int, double[], int) -
Method in class org.netlib.blas.BLAS
-
..
- dtbrfs(String, String, String, int, int, int, double[], int, double[], int, double[], int, double[], double[], double[], int[], intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dtbsv(String, String, String, int, int, double[], int, double[], int) -
Method in class org.netlib.blas.BLAS
-
..
- dtbtrs(String, String, String, int, int, int, double[], int, double[], int, intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dtgevc(String, String, boolean[], int, double[], int, double[], int, double[], int, double[], int, int, intW, double[], intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dtgex2(boolean, boolean, int, double[], int, double[], int, double[], int, double[], int, int, int, int, double[], int, intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dtgexc(boolean, boolean, int, double[], int, double[], int, double[], int, double[], int, intW, intW, double[], int, intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dtgsen(int, boolean, boolean, boolean[], int, double[], int, double[], int, double[], double[], double[], double[], int, double[], int, intW, doubleW, doubleW, double[], double[], int, int[], int, intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dtgsja(String, String, String, int, int, int, int, int, double[], int, double[], int, double, double, double[], double[], double[], int, double[], int, double[], int, double[], intW, intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dtgsna(String, String, boolean[], int, double[], int, double[], int, double[], int, double[], int, double[], double[], int, intW, double[], int, int[], intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dtgsy2(String, int, int, int, double[], int, double[], int, double[], int, double[], int, double[], int, double[], int, doubleW, doubleW, doubleW, int[], intW, intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dtgsyl(String, int, int, int, double[], int, double[], int, double[], int, double[], int, double[], int, double[], int, doubleW, doubleW, double[], int, int[], intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dtpcon(String, String, String, int, double[], doubleW, double[], int[], intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dtpmv(String, String, String, int, double[], double[], int) -
Method in class org.netlib.blas.BLAS
-
..
- dtprfs(String, String, String, int, int, double[], double[], int, double[], int, double[], double[], double[], int[], intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dtpsv(String, String, String, int, double[], double[], int) -
Method in class org.netlib.blas.BLAS
-
..
- dtptri(String, String, int, double[], intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dtptrs(String, String, String, int, int, double[], double[], int, intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dtrcon(String, String, String, int, double[], int, doubleW, double[], int[], intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dtrevc(String, String, boolean[], int, double[], int, double[], int, double[], int, int, intW, double[], intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dtrexc(String, int, double[], int, double[], int, intW, intW, double[], intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dtrmm(String, String, String, String, int, int, double, double[], int, double[], int) -
Method in class org.netlib.blas.BLAS
-
..
- dtrmv(boolean, boolean, boolean, DoubleMatrix2D, DoubleMatrix1D) -
Method in interface cern.colt.matrix.linalg.Blas
- Triangular matrix-vector multiplication; x = A*x or x = A'*x.
- dtrmv(boolean, boolean, boolean, DoubleMatrix2D, DoubleMatrix1D) -
Method in class cern.colt.matrix.linalg.SeqBlas
-
- dtrmv(boolean, boolean, boolean, DoubleMatrix2D, DoubleMatrix1D) -
Method in class cern.colt.matrix.linalg.SmpBlas
-
- dtrmv(boolean, boolean, boolean, DoubleMatrix2D, DoubleMatrix1D) -
Method in interface cern.colt.matrix.tdouble.algo.DoubleBlas
- Triangular matrix-vector multiplication; x = A*x or x = A'*x.
- dtrmv(boolean, boolean, boolean, DoubleMatrix2D, DoubleMatrix1D) -
Method in class cern.colt.matrix.tdouble.algo.SmpDoubleBlas
-
- dtrmv(boolean, boolean, boolean, FloatMatrix2D, FloatMatrix1D) -
Method in interface cern.colt.matrix.tfloat.algo.FloatBlas
- Triangular matrix-vector multiplication; x = A*x or x = A'*x.
- dtrmv(boolean, boolean, boolean, FloatMatrix2D, FloatMatrix1D) -
Method in class cern.colt.matrix.tfloat.algo.SmpFloatBlas
-
- dtrmv(String, String, String, int, double[], int, double[], int) -
Method in class org.netlib.blas.BLAS
-
..
- dtrrfs(String, String, String, int, int, double[], int, double[], int, double[], int, double[], double[], double[], int[], intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dtrsen(String, String, boolean[], int, double[], int, double[], int, double[], double[], intW, doubleW, doubleW, double[], int, int[], int, intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dtrsm(String, String, String, String, int, int, double, double[], int, double[], int) -
Method in class org.netlib.blas.BLAS
-
..
- dtrsna(String, String, boolean[], int, double[], int, double[], int, double[], int, double[], double[], int, intW, double[], int, int[], intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dtrsv(String, String, String, int, double[], int, double[], int) -
Method in class org.netlib.blas.BLAS
-
..
- dtrsyl(String, String, int, int, int, double[], int, double[], int, double[], int, doubleW, intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dtrti2(String, String, int, double[], int, intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dtrtri(String, String, int, double[], int, intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dtrtrs(String, String, String, int, int, double[], int, double[], int, intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dtzrqf(int, int, double[], int, double[], intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dtzrzf(int, int, double[], int, double[], double[], int, intW) -
Method in class org.netlib.lapack.LAPACK
-
..
- dualPartition(double[], double[], int, int, double[], int, int, int[]) -
Static method in class cern.colt.Partitioning
- Same as
Partitioning.dualPartition(int[],int[],int,int,int[],int,int,int[])
except that it synchronously partitions double[] rather
than int[] arrays.
- dualPartition(double[], double[], int, int, double) -
Static method in class cern.colt.Partitioning
- Same as
Partitioning.dualPartition(int[],int[],int,int,int)
except that it
synchronously partitions double[] rather than
int[] arrays.
- dualPartition(int[], int[], int, int, int[], int, int, int[]) -
Static method in class cern.colt.Partitioning
- Same as
Partitioning.partition(int[],int,int,int[],int,int,int[])
except that
this method synchronously partitions two arrays at the same time;
both arrays are partially sorted according to the elements of the primary
array.
- dualPartition(int[], int[], int, int, int) -
Static method in class cern.colt.Partitioning
- Same as
Partitioning.partition(int[],int,int,int)
except that this method
synchronously partitions two arrays at the same time; both arrays
are partially sorted according to the elements of the primary array.
- DummyLocalizable - Class in org.apache.commons.math.exception.util
- Dummy implementation of the
Localizable
interface, without localization. - DummyLocalizable(String) -
Constructor for class org.apache.commons.math.exception.util.DummyLocalizable
- Simple constructor.
- DummyStepHandler - Class in org.apache.commons.math.ode.sampling
- This class is a step handler that does nothing.
- DummyStepInterpolator - Class in org.apache.commons.math.ode.sampling
- This class is a step interpolator that does nothing.
- DummyStepInterpolator() -
Constructor for class org.apache.commons.math.ode.sampling.DummyStepInterpolator
- Simple constructor.
- DummyStepInterpolator(double[], double[], boolean) -
Constructor for class org.apache.commons.math.ode.sampling.DummyStepInterpolator
- Simple constructor.
- DummyStepInterpolator(DummyStepInterpolator) -
Constructor for class org.apache.commons.math.ode.sampling.DummyStepInterpolator
- Copy constructor.
- DuplicateSampleAbscissaException - Exception in org.apache.commons.math
- Exception thrown when a sample contains several entries at the same abscissa.
- DuplicateSampleAbscissaException(double, int, int) -
Constructor for exception org.apache.commons.math.DuplicateSampleAbscissaException
- Construct an exception indicating the duplicate abscissa.
- durbinWatson(DoubleArrayList) -
Static method in class cern.jet.stat.Descriptive
- Durbin-Watson computation.
- durbinWatson(DoubleArrayList) -
Static method in class cern.jet.stat.tdouble.DoubleDescriptive
- Durbin-Watson computation.
- durbinWatson(FloatArrayList) -
Static method in class cern.jet.stat.tfloat.FloatDescriptive
- Durbin-Watson computation.
- dvout(int, int, double[], int, String) -
Method in class org.netlib.arpack.ARPACK
- No documentation was available when generating this method.
- DynamicBin1D - Class in cern.hep.aida.bin
- 1-dimensional rebinnable bin holding double elements;
Efficiently computes advanced statistics of data sequences.
- DynamicBin1D() -
Constructor for class cern.hep.aida.bin.DynamicBin1D
- Constructs and returns an empty bin; implicitly calls
setFixedOrder(false)
.
- DynamicDoubleBin1D - Class in hep.aida.tdouble.bin
- 1-dimensional rebinnable bin holding double elements; Efficiently
computes advanced statistics of data sequences.
- DynamicDoubleBin1D() -
Constructor for class hep.aida.tdouble.bin.DynamicDoubleBin1D
- Constructs and returns an empty bin; implicitly calls
setFixedOrder(false)
.
- DynamicFloatBin1D - Class in hep.aida.tfloat.bin
- 1-dimensional rebinnable bin holding float elements; Efficiently
computes advanced statistics of data sequences.
- DynamicFloatBin1D() -
Constructor for class hep.aida.tfloat.bin.DynamicFloatBin1D
- Constructs and returns an empty bin; implicitly calls
setFixedOrder(false)
.
E
(0, 6, x).
E
(fieldwidth, 6, x).
e
(0, 6, x).
e
(fieldwidth, 6, x).
TallyStore
object.
DiscreteDistribution
to an empirical
distribution function,
based on the observations
X(1),..., X(n) (sorted by increasing order).EmpiricalDistribution
interface.PointSetRandomization
.file
.
formatp0
to determine
which p-values are too close to 0 or 1 to be printed explicitly.
object
is a
FieldMatrix
instance with the same dimensions as this
and all corresponding matrix entries are equal.
object
is a
RealMatrix
instance with the same dimensions as this
and all corresponding matrix entries are equal.
object
is a
BigMatrixImpl
instance with the same dimensions as this
and all corresponding matrix entries are equal.
a.subtract(b
} to be the zero vector, while
a.equals(b) == false
.
object
is an
AbstractStorelessUnivariateStatistic
returning the same
values as this for getResult()
and getN()
object
is a MultivariateSummaryStatistics
instance and all statistics have the same values as this.
object
is a
StatisticalSummaryValues
instance and all statistics have
the same values as this.
object
is a
SummaryStatistics
instance and all statistics have the
same values as this.
object
is a MultivariateSummaryStatistics
instance and all statistics have the same values as this.
object
is a
SummaryStatistics
instance and all statistics have the
same values as this.
NaN == NaN
. In release
3.0, the semantics will change in order to comply with IEEE754 where it
is specified that NaN != NaN
.
New methods have been added for those cases wher the old semantics is
useful (see e.g. equalsIncludingNaN
.
NaN == NaN
. In release
3.0, the semantics will change in order to comply with IEEE754 where it
is specified that NaN != NaN
.
New methods have been added for those cases where the old semantics is
useful (see e.g. equalsIncludingNaN
.
MathUtils.equals(double,double)
.
equals(x, y, 1)
.
equals(x, y, maxUlps)
.
MathUtils.equalsIncludingNaN(float,float)
.
equals(x, y, 1)
.
equals(x, y, maxUlps
.
MathUtils.equalsIncludingNaN(double,double)
.
GammaDist
for the special case
of the Erlang distribution with
shape parameter k > 0 and scale parameter
λ > 0.Clusterable
for points with integer coordinates.interpol
(n, X, Y, C), this
function returns the value of the interpolating polynomial P(z) evaluated
at z (see eq.
AbstractStorelessUnivariateStatistic.clear()
, then invokes
AbstractStorelessUnivariateStatistic.increment(double)
in a loop over the the input array, and then uses
AbstractStorelessUnivariateStatistic.getResult()
to compute the return value.
AbstractStorelessUnivariateStatistic.clear()
, then invokes
AbstractStorelessUnivariateStatistic.increment(double)
in a loop over the specified portion of the input
array, and then uses AbstractStorelessUnivariateStatistic.getResult()
to compute the return value.
Double.NaN
if the designated subarray
is empty.
Double.NaN
if the designated subarray
is empty.
SemiVariance
for the entire array against the mean, using
instance properties varianceDirection and biasCorrection.
SemiVariance
of the designated values against the mean, using
instance properties varianceDirection and biasCorrection.
SemiVariance
for the entire array against the mean, using
the current value of the biasCorrection instance property.
SemiVariance
of the designated values against the cutoff, using
instance properties variancDirection and biasCorrection.
SemiVariance
of the designated values against the cutoff in the
given direction, using the current value of the biasCorrection instance property.
SemiVariance
of the designated values against the cutoff
in the given direction with the provided bias correction.
Double.NaN
if the array is empty.
Double.NaN
if the designated subarray
is empty.
Double.NaN
if the array is empty.
Double.NaN
if the designated subarray
is empty.
Double.NaN
if the designated subarray
is empty.
Double.NaN
if the designated subarray
is empty.
Double.NaN
if the designated subarray
is empty.
p
th percentile of the values
in the values
array.
quantile
th percentile of the
designated values in the values
array.
p
th percentile of the values
in the values
array, starting with the element in (0-based)
position begin
in the array and including length
values.
Double.NaN
if the designated subarray
is empty.
Double.NaN
if the designated subarray
is empty.
Double.NaN
if the designated subarray
is empty.
Double.NaN
if the designated subarray
is empty.
Double.NaN
if the designated subarray
is empty.
Double.NaN
if the designated subarray
is empty.
EventHandler
EventException.EventException(Localizable, Object...)
event handler
during integration steps.actions
method.
FastMath.exp
method wrapped as a ComposableFunction
.
FastMath.expm1
method wrapped as a ComposableFunction
.
ContinuousDistribution
for
the exponential distribution
with mean 1/λ where
λ > 0.ExponentialDist
class with a constructor accepting as
argument the mean 1/λ instead of the rate λ.ExponentialDistribution
.GumbelDist
.
GumbelDist
.
f
(0, 6, x).
f
(fieldwidth, 6, x).
RandomStream
interface by using as a backbone
generator the combination of the WELL607 proposed in
(and implemented in WELL607
) with a nonlinear generator.F2wNetLFSR
,
F2wNetPolyLCG
,
F2wCycleBasedLFSR
and
F2wCycleBasedPolyLCG
.StrictMath
.ContinuousDistribution
for
the fatigue life distribution with location
parameter μ, scale parameter β and shape
parameter γ.FaureSequence
(b, k, w, w, dim)
with base b equal to the smallest prime larger or equal to dim,
and with at least n points.
FDist
, except that it provides static methods
to compute or approximate the complementary distribution function of X,
which we define as
bar(F)(x) = P[X >= x], instead of
F(x) = P[X <= x].FDistribution
.length
with values generated
using getNext() repeatedly.
FirstMoment
identical
to the original
ContinuousDistribution
for
the Fisher F distribution with n and m
degrees of freedom, where n and m are positive integers.float
elements; implemented with arrays.float
elements; implemented with arrays.AbstractFloatList
to be viewed and treated as a JDK 1.2 AbstractList
.AbstractFloatList
to be
viewed and treated as a JDK 1.2 AbstractList
.FloatMersenneTwister
seeded
with the given seed.
long <= value
.
long <= value
.
long <= value
.
FastMath.floor
method wrapped as a ComposableFunction
.
ContinuousDistribution
for
the folded normal distribution with
parameters μ >= 0 and
σ > 0.Complex
object to produce a string.
BigFraction
object to produce a string.
Fraction
object to produce a string.
BigFraction
object to produce a string.
Fraction
object to produce a string.
Vector3D
object to produce a string.
RealVector
object to produce a string.
init
for this AbstractChrono to a
String
in the HH:MM:SS.xx format.
String
in the HH:MM:SS.xx format.
d
(0, 1, x).
String
with a minimum length
of fieldwidth, the result is right-padded with spaces if
necessary but it is not truncated.
String
containing x.
format
, except it formats the given
value for the locale locale.
String
containing the elements n1
to n2 (inclusive) of table V,
k elements per line, p positions per element.
formatBase
(0, b, x).
String
representation in base
b.
Format.format(Object)
on a default instance of
ComplexFormat.
formatKS
,
but for the KS statistic DN+(a).
formatKS
,
but for DN+(a).
formatp0
to print p, and adds
the marker ``****'' if p is considered suspect
(uses the environment variable RSUSPECTP for this).
formatp1
.
formatPoints
(n, d) with n and d equal to the
number of points and the dimension of this object, respectively.
toString
, together with the first d coordinates of the
first n points.
formatPoints
(iter, n, d)
with n and d equal to the number of points and the dimension, respectively.
formatPoints
(n, d), but
prints the points by calling iter repeatedly.
formatPoints
(), but the
points coordinates are printed in base b.
formatPoints
(n, d), but the
points coordinates are printed in base b.
formatPoints
(iter),
but the points coordinates are printed in base b.
formatPoints
(iter, n, d),
but the points coordinates are printed in base b.
formatPointsNumbered
(n, d)
with n and d equal to the number of points and the dimension,
respectively.
formatPoints
(n,d), except that the points are numbered.
Format.format(Object)
on a default instance of
RealVectorFormat.
Format.format(Object)
on a default instance of
Vector3DFormat.
formatWithError
,
except that it formats the given value and error for the
locale locale.
formatWithError
,
except that it formats the given value and error for the
locale locale.
Former
via
method create(); Serves to isolate the interface of String formatting from
the actual implementation.Former
via method create();
Implementations of can use existing libraries such as corejava.PrintfFormat or corejava.Format or other.FourthMoment
identical
to the original
FieldMatrix
/Fraction
matrix to a RealMatrix
.
ContinuousDistribution
for the Fréchet
distribution, with location parameter δ, scale
parameter β > 0, and shape parameter
α > 0, where we use
the notation
z = (x - δ)/β.G
(0, 6, x).
G
(fieldwidth, 6, x).
g
(0, 6, x).
g
(fieldwidth, 6, x).
ContinuousDistribution
for
the gamma distribution with
shape parameter
α > 0 and scale parameter
λ > 0.GammaDist
distribution with constructors accepting the
mean μ and variance σ2 as arguments instead of a shape parameter
α and a scale parameter λ.GammaDistribution
.GammaProcessPCA
, but the generated uniforms
correspond to a bridge transformation of the BrownianMotionPCA
instead of a sequential transformation.GammaProcessPCABridge
, but uses the fast inversion method
for the symmetrical beta distribution, proposed by L'Ecuyer and Simard, to accelerate the generation of the beta random variables.GaussianFunction
.GaussianFunction
).a
, b
, c
, and d
)
of a ParametricGaussianFunction
based on the specified observed
points.gaussLobatto
(MathFunction, double, double, double), but
also returns in T[0] the subintervals of integration, and in
T[1], the partial values of the integral over the corresponding
subintervals.
RandomStream
's.
Partitioning.partition(int[],int,int,int[],int,int,int[])
except that
it generically partitions arbitrary shaped data (for example
matrices or multiple arrays) rather than int[] arrays.
RandomStream
interface via inheritance
from RandomStreamBase
.BrownianMotion
.
DiscreteDistributionInt
for
the geometric distribution with parameter
p, where 0 < p < 1.GeometricMean
identical
to the original
Double.NaN
if the array is empty.
Double.NaN
if the designated subarray
is empty.
SummaryStatistics
containing statistics describing the values in each of the bins.
SummaryStatistics
instances containing
statistics describing the values in each of the bins.
BrownianMotionPCA
that is included in the
GammaProcessPCA
object.
BrownianMotionPCA
.
BrownianMotion
object
used to generate the process.
BrownianMotion
.
BrownianMotionPCA
.
StringBuffer
associated with that object.
col
as an array.
col
as an array.
col
as an array.
col
as an array.
col
as an array.
col
as an array.
col
as an array.
col
as an array.
col
as an array
of double values.
col
as an array
of double values.
column
as a column matrix.
column
as a column matrix.
column
as a column matrix.
column
as a column matrix.
column
as a column matrix.
column
as a column matrix.
column
as a column matrix.
column
as a column matrix.
column
as a vector.
column
as a vector.
column
as a vector.
column
as a vector.
column
as a vector.
column
as a vector.
ContinuousDistribution
object by executing the code contained in the string str.
getCorrelationStandardErrors().getEntry(i,j)
is the standard
error associated with getCorrelationMatrix.getEntry(i,j)
Frequency.getCount(Comparable)
as of 2.0
Frequency.getCumFreq(Comparable)
as of 2.0
Frequency.getCumPct(Comparable)
as of 2.0
Sim
.
BigInteger
.
new LUDecompositionImpl(m)
.getDeterminant()
getContinuousDistribution
, but for discrete distributions
over the real numbers.
getContinuousDistribution
, but for discrete distributions
over the integers.
Distribution
used by this generator.
DiscreteDistributionInt
used by this generator.
DoubleArrayList
object that contains the observations for this probe.
DoubleArray
.
ResizableArray
.
expansionMode
determines whether the internal storage
array grows additively (ADDITIVE_MODE) or multiplicatively
(MULTIPLICATIVE_MODE) when it is expanded.
BracketFinder.getHi()
.
Field
to which the instance belongs.
Field
(really a DfpField
) to which the instance belongs.
Field
to which the instance belongs.
Field
to which the instance belongs.
Field
to which the instance belongs.
Field
to which the instance belongs.
getField
,
except that it can return non-public fields.
Polynomial
instance used to evaluate
x, in an ArrayList table instance returned by
getSplinePolynomials().
BracketFinder.getLo()
.
BracketFinder.getMid()
.
GammaProcess
.
NormalGen
used.
StoppingCondition
in the last run.
MultivariateSummaryStatistics.addValue(double[])
MultivariateSummaryStatistics.addValue(double[])
GammaProcess
object gneg
used to generate the
Γ- component of the process.
GammaProcess
object gpos
used to generate the
Γ+ component of the process.
init
for this AbstractChrono.
initStat
was called.
getInstanceFromMLE
, but for the case β < 0.
data[p[0]],..,data[p[data.length-1]]
data.get(p[0]),..,data.get(p[data.length-1])
update
method (or the initial value if
update
was never called after init
).
MultivariateSummaryStatistics.addValue(double[])
MultivariateSummaryStatistics.addValue(double[])
MultivariateSummaryStatistics.addValue(double[])
MultivariateSummaryStatistics.addValue(double[])
getMethod
, except that it can return non-public methods.
MultivariateSummaryStatistics.addValue(double[])
MultivariateSummaryStatistics.addValue(double[])
init
for this AbstractChrono.
getMLE
, but for the case β < 0.
BigInteger
.
optimize
.
optimize
.
optimize
.
optimize
.
optimize
.
theoretical value
according to the parameter.
MathException.getSpecificPattern()
and MathException.getGeneralPattern()
MathRuntimeException.getSpecificPattern()
and MathRuntimeException.getGeneralPattern()
Frequency.getPct(Comparable)
as of 2.0
Dfp
instances built by this factory.
PearsonsCorrelation
instance constructed from the
ranked input data.
BigFraction
instance with the 2 parts of a fraction
Y/Z.
Fraction
instance with the 2 parts
of a fraction Y/Z.
BigDecimal.ROUND_HALF_UP
RoundingMode.HALF_UP
row
as an array.
row
as an array.
row
as an array.
row
as an array.
row
as an array.
row
as an array.
row
as an array.
row
as an array.
row
as an array
of double values.
row
as an array
of double values.
row
as a row matrix.
row
as a row matrix.
row
as a row matrix.
row
as a row matrix.
row
as a row matrix.
row
as a row matrix.
row
as a row matrix.
row
as a row matrix.
row
as a vector.
row
as a vector.
row
as a vector.
row
as a vector.
row
as a vector.
row
as a vector.
StatisticalSummary
describing this distribution.
StatisticalSummary
describing this distribution.
init
for this AbstractChrono.
OpenMapRealVector.getSparsity()
MultivariateSummaryStatistics.addValue(double[])
MultivariateSummaryStatistics.addValue(double[])
RandomStream
.
RandomStream
.
RandomStream
.
RandomStream
used by this generator.
RandomStream
used by this object.
RandomStream
stream.
RandomStream
for the underlying Brownian motion.
RandomStream
's are the same.
InverseGaussianProcess
.
BrownianMotion
process, which should
be the same as for the GammaProcess
.
MultivariateSummaryStatistics.addValue(double[])
MultivariateSummaryStatistics.addValue(double[])
MultivariateSummaryStatistics.addValue(double[])
MultivariateSummaryStatistics.addValue(double[])
StatisticalSummaryValues
instance reporting current
aggregate statistics.
StatisticalSummaryValues
instance reporting current
statistics.
StatisticalSummaryValues
instance reporting current
statistics.
MultivariateSummaryStatistics.addValue(double[])
MultivariateSummaryStatistics.addValue(double[])
ResizableDoubleArray.getInternalValues()
as of 2.0
valuesFileURL
- getValuesList(int) -
Method in class umontreal.iro.lecuyer.charts.CustomHistogramDataset
- Returns the values for a series.
- getValuesList(int) -
Method in class umontreal.iro.lecuyer.charts.HistogramSeriesCollection
- Returns the values for a series.
- getVariance() -
Method in class jhplot.math.num.pdf.NegativeBinomial
- Get mean value.
- getVariance() -
Method in class org.apache.commons.math.stat.descriptive.AggregateSummaryStatistics
- Returns the variance of the available values.
- getVariance() -
Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
- Returns the variance of the available values.
- getVariance() -
Method in interface org.apache.commons.math.stat.descriptive.StatisticalSummary
- Returns the variance of the available values.
- getVariance() -
Method in class org.apache.commons.math.stat.descriptive.StatisticalSummaryValues
-
- getVariance() -
Method in class org.apache.commons.math.stat.descriptive.SummaryStatistics
- Returns the variance of the values that have been added.
- getVariance() -
Method in class org.apache.commons.math.stat.descriptive.SynchronizedSummaryStatistics
- Returns the variance of the values that have been added.
- getVariance() -
Method in class umontreal.iro.lecuyer.probdist.BernoulliDist
-
- getVariance(double) -
Static method in class umontreal.iro.lecuyer.probdist.BernoulliDist
- Computes the variance
Var[X] = p(1 - p) of the Bernoulli
distribution with parameter p.
- getVariance() -
Method in class umontreal.iro.lecuyer.probdist.BetaDist
-
- getVariance(double, double) -
Static method in class umontreal.iro.lecuyer.probdist.BetaDist
- .
- getVariance(double, double, double, double) -
Static method in class umontreal.iro.lecuyer.probdist.BetaDist
- .
- getVariance() -
Method in class umontreal.iro.lecuyer.probdist.BetaSymmetricalDist
-
- getVariance(double) -
Static method in class umontreal.iro.lecuyer.probdist.BetaSymmetricalDist
- Computes and returns the variance,
Var[X] = 1/(8α + 4),
of the symmetrical beta distribution with parameter α.
- getVariance() -
Method in class umontreal.iro.lecuyer.probdist.BinomialDist
-
- getVariance(int, double) -
Static method in class umontreal.iro.lecuyer.probdist.BinomialDist
- Computes the variance
Var[X] = np(1 - p) of the binomial
distribution with parameters n and p.
- getVariance() -
Method in class umontreal.iro.lecuyer.probdist.CauchyDist
-
- getVariance(double, double) -
Static method in class umontreal.iro.lecuyer.probdist.CauchyDist
- Returns ∞ since the variance does not exist.
- getVariance() -
Method in class umontreal.iro.lecuyer.probdist.ChiDist
-
- getVariance(int) -
Static method in class umontreal.iro.lecuyer.probdist.ChiDist
- Computes and returns the variance
of the chi distribution with parameter ν.
- getVariance() -
Method in class umontreal.iro.lecuyer.probdist.ChiSquareDist
-
- getVariance(int) -
Static method in class umontreal.iro.lecuyer.probdist.ChiSquareDist
- Returns the variance
Var[X] = 2n
of the chi-square distribution with parameter n.
- getVariance() -
Method in class umontreal.iro.lecuyer.probdist.ChiSquareNoncentralDist
-
- getVariance(double, double) -
Static method in class umontreal.iro.lecuyer.probdist.ChiSquareNoncentralDist
- Computes and returns the variance
Var[X] = 2(ν +2λ) of the noncentral chi-square distribution with parameters
ν = nu and λ = lambda.
- getVariance() -
Method in class umontreal.iro.lecuyer.probdist.ContinuousDistribution
- Returns the variance.
- getVariance() -
Method in class umontreal.iro.lecuyer.probdist.CramerVonMisesDist
-
- getVariance(int) -
Static method in class umontreal.iro.lecuyer.probdist.CramerVonMisesDist
- Returns the variance of the distribution with parameter n.
- getVariance() -
Method in class umontreal.iro.lecuyer.probdist.DiscreteDistribution
- Computes the variance
Var[X] = ∑i=1npi(xi - E[X])2
of the distribution.
- getVariance() -
Method in interface umontreal.iro.lecuyer.probdist.Distribution
- Returns the variance of the distribution function.
- getVariance() -
Method in class umontreal.iro.lecuyer.probdist.EmpiricalDist
-
- getVariance(int, double) -
Static method in class umontreal.iro.lecuyer.probdist.ErlangDist
- Computes and returns the variance,
Var[X] = k/λ2,
of the Erlang distribution with parameters k and λ.
- getVariance() -
Method in class umontreal.iro.lecuyer.probdist.ExponentialDist
-
- getVariance(double) -
Static method in class umontreal.iro.lecuyer.probdist.ExponentialDist
- Computes and returns the variance,
Var[X] = 1/λ2,
of the exponential distribution with parameter λ.
- getVariance() -
Method in class umontreal.iro.lecuyer.probdist.ExtremeValueDist
- Deprecated.
- getVariance(double, double) -
Static method in class umontreal.iro.lecuyer.probdist.ExtremeValueDist
- Deprecated. Computes and returns the variance,
Var[X] = π2/(6λ2),
of the extreme value distribution with parameters α and λ.
- getVariance() -
Method in class umontreal.iro.lecuyer.probdist.FatigueLifeDist
-
- getVariance(double, double, double) -
Static method in class umontreal.iro.lecuyer.probdist.FatigueLifeDist
- Computes and returns the variance
Var[X] = β2γ2(1 + 5γ2/4) of the fatigue life distribution
with parameters μ, β and γ.
- getVariance() -
Method in class umontreal.iro.lecuyer.probdist.FisherFDist
-
- getVariance(int, int) -
Static method in class umontreal.iro.lecuyer.probdist.FisherFDist
- Computes and returns the variance
of the Fisher F distribution with parameters n and m.
- getVariance() -
Method in class umontreal.iro.lecuyer.probdist.FoldedNormalDist
-
- getVariance(double, double) -
Static method in class umontreal.iro.lecuyer.probdist.FoldedNormalDist
- .
- getVariance() -
Method in class umontreal.iro.lecuyer.probdist.FrechetDist
-
- getVariance(double, double, double) -
Static method in class umontreal.iro.lecuyer.probdist.FrechetDist
- Returns the variance of the Fréchet distribution with parameters
α, β and δ.
- getVariance() -
Method in class umontreal.iro.lecuyer.probdist.GammaDist
-
- getVariance(double, double) -
Static method in class umontreal.iro.lecuyer.probdist.GammaDist
- Computes and returns the variance
Var[X] = α/λ2
of the gamma distribution with parameters α and λ.
- getVariance() -
Method in class umontreal.iro.lecuyer.probdist.GeometricDist
-
- getVariance(double) -
Static method in class umontreal.iro.lecuyer.probdist.GeometricDist
- Computes and returns the variance
Var[X] = (1 - p)/p2
of the geometric distribution with parameter p.
- getVariance() -
Method in class umontreal.iro.lecuyer.probdist.GumbelDist
-
- getVariance(double, double) -
Static method in class umontreal.iro.lecuyer.probdist.GumbelDist
- Returns the variance
Var[X] = π2β2/6 of the Gumbel distribution with parameters β and δ.
- getVariance() -
Method in class umontreal.iro.lecuyer.probdist.HalfNormalDist
-
- getVariance(double, double) -
Static method in class umontreal.iro.lecuyer.probdist.HalfNormalDist
- Computes and returns the variance
Var[X] = (1 - 2/π)σ2.
- getVariance() -
Method in class umontreal.iro.lecuyer.probdist.HyperbolicSecantDist
-
- getVariance(double, double) -
Static method in class umontreal.iro.lecuyer.probdist.HyperbolicSecantDist
- Computes and returns the variance
Var[X] = σ2
of the hyperbolic secant distribution with parameters μ and σ.
- getVariance() -
Method in class umontreal.iro.lecuyer.probdist.HypergeometricDist
-
- getVariance(int, int, int) -
Static method in class umontreal.iro.lecuyer.probdist.HypergeometricDist
- Computes and returns the variance
of the hypergeometric distribution with parameters m, l and k.
- getVariance() -
Method in class umontreal.iro.lecuyer.probdist.InverseGammaDist
-
- getVariance(double, double) -
Static method in class umontreal.iro.lecuyer.probdist.InverseGammaDist
- Returns the variance
Var[X] = β2/((α -1)2(α - 2))
of the inverse gamma distribution with shape parameter α and scale
parameter β.
- getVariance() -
Method in class umontreal.iro.lecuyer.probdist.InverseGaussianDist
-
- getVariance(double, double) -
Static method in class umontreal.iro.lecuyer.probdist.InverseGaussianDist
- Computes and returns the variance
Var[X] = μ3/λ of
the inverse gaussian distribution with parameters μ and λ.
- getVariance() -
Method in class umontreal.iro.lecuyer.probdist.JohnsonSUDist
-
- getVariance(double, double, double, double) -
Static method in class umontreal.iro.lecuyer.probdist.JohnsonSUDist
- Computes and returns the variance
of the Johnson SU distribution with parameters γ, δ, ξ and λ.
- getVariance() -
Method in class umontreal.iro.lecuyer.probdist.LaplaceDist
-
- getVariance(double, double) -
Static method in class umontreal.iro.lecuyer.probdist.LaplaceDist
- Computes and returns the variance
Var[X] = 2β2
of the Laplace distribution with parameters μ and β.
- getVariance() -
Method in class umontreal.iro.lecuyer.probdist.LogarithmicDist
-
- getVariance(double) -
Static method in class umontreal.iro.lecuyer.probdist.LogarithmicDist
- Computes and returns the variance
of the logarithmic distribution with parameter θ = theta.
- getVariance() -
Method in class umontreal.iro.lecuyer.probdist.LogisticDist
-
- getVariance(double, double) -
Static method in class umontreal.iro.lecuyer.probdist.LogisticDist
- Computes and returns the variance
Var[X] = π2/(3λ2) of the logistic distribution
with parameters α and λ.
- getVariance() -
Method in class umontreal.iro.lecuyer.probdist.LoglogisticDist
-
- getVariance(double, double) -
Static method in class umontreal.iro.lecuyer.probdist.LoglogisticDist
- Computes and returns the variance
of the log-logistic distribution with parameters α and β.
- getVariance() -
Method in class umontreal.iro.lecuyer.probdist.LognormalDist
-
- getVariance(double, double) -
Static method in class umontreal.iro.lecuyer.probdist.LognormalDist
- Computes and returns the variance
Var[X] = e2μ+σ2(eσ2 - 1)
of the lognormal distribution with parameters μ and σ.
- getVariance() -
Method in class umontreal.iro.lecuyer.probdist.NakagamiDist
-
- getVariance(double, double, double) -
Static method in class umontreal.iro.lecuyer.probdist.NakagamiDist
- .
- getVariance() -
Method in class umontreal.iro.lecuyer.probdist.NegativeBinomialDist
-
- getVariance(double, double) -
Static method in class umontreal.iro.lecuyer.probdist.NegativeBinomialDist
- Computes and returns the variance
Var[X] = γ(1 - p)/p2
of the negative binomial distribution with parameters γ and p.
- getVariance() -
Method in class umontreal.iro.lecuyer.probdist.NormalDist
-
- getVariance(double, double) -
Static method in class umontreal.iro.lecuyer.probdist.NormalDist
- Computes and returns the variance
Var[X] = σ2 of the
normal distribution with parameters μ and σ.
- getVariance() -
Method in class umontreal.iro.lecuyer.probdist.NormalInverseGaussianDist
-
- getVariance(double, double, double, double) -
Static method in class umontreal.iro.lecuyer.probdist.NormalInverseGaussianDist
- Computes and returns the variance
Var[X] = δα2/γ3 of the normal inverse gaussian distribution with parameters
α, β, μ and δ.
- getVariance() -
Method in class umontreal.iro.lecuyer.probdist.ParetoDist
-
- getVariance(double, double) -
Static method in class umontreal.iro.lecuyer.probdist.ParetoDist
- Computes and returns the variance
of the Pareto distribution with parameters α and β.
- getVariance() -
Method in class umontreal.iro.lecuyer.probdist.Pearson5Dist
-
- getVariance(double, double) -
Static method in class umontreal.iro.lecuyer.probdist.Pearson5Dist
- Computes and returns the variance
Var[X] = β2/((α -1)2(α - 2)
of a Pearson V distribution with shape parameter α and scale
parameter β.
- getVariance() -
Method in class umontreal.iro.lecuyer.probdist.Pearson6Dist
-
- getVariance(double, double, double) -
Static method in class umontreal.iro.lecuyer.probdist.Pearson6Dist
- Computes and returns the variance
Var[X] = [β2α1(α1 + α2 -1)]/[(α2 -1)2(α2 - 2)] of a Pearson VI distribution with shape
parameters α1 and α2, and scale parameter β.
- getVariance() -
Method in class umontreal.iro.lecuyer.probdist.PiecewiseLinearEmpiricalDist
-
- getVariance() -
Method in class umontreal.iro.lecuyer.probdist.PoissonDist
-
- getVariance(double) -
Static method in class umontreal.iro.lecuyer.probdist.PoissonDist
- Computes and returns the variance = λ
of the Poisson distribution with parameter λ.
- getVariance() -
Method in class umontreal.iro.lecuyer.probdist.PowerDist
-
- getVariance(double, double, double) -
Static method in class umontreal.iro.lecuyer.probdist.PowerDist
- Computes and returns the variance
(b - a)2c/[(c + 1)2(c + 2)]
of the power distribution with parameters a, b and c.
- getVariance() -
Method in class umontreal.iro.lecuyer.probdist.RayleighDist
-
- getVariance(double) -
Static method in class umontreal.iro.lecuyer.probdist.RayleighDist
- Returns the variance
of the Rayleigh distribution with parameter β.
- getVariance() -
Method in class umontreal.iro.lecuyer.probdist.StudentDist
-
- getVariance(int) -
Static method in class umontreal.iro.lecuyer.probdist.StudentDist
- Computes and returns the variance
Var[X] = n/(n - 2)
of the Student t-distribution with parameter n.
- getVariance() -
Method in class umontreal.iro.lecuyer.probdist.TriangularDist
-
- getVariance(double, double, double) -
Static method in class umontreal.iro.lecuyer.probdist.TriangularDist
- Computes and returns the variance
Var[X] = (a2 + b2 + m2 - ab - am - bm)/18
of the triangular distribution with parameters a, b, m.
- getVariance() -
Method in class umontreal.iro.lecuyer.probdist.TruncatedDist
- Returns an approximation of the variance computed with the
Simpson 1/3 numerical integration rule.
- getVariance() -
Method in class umontreal.iro.lecuyer.probdist.UniformDist
-
- getVariance(double, double) -
Static method in class umontreal.iro.lecuyer.probdist.UniformDist
- Computes and returns the variance
Var[X] = (b - a)2/12
of the uniform distribution with parameters a and b.
- getVariance() -
Method in class umontreal.iro.lecuyer.probdist.UniformIntDist
-
- getVariance(int, int) -
Static method in class umontreal.iro.lecuyer.probdist.UniformIntDist
- Computes and returns the variance
Var[X] = [(j - i + 1)2 -1]/12
of the discrete uniform distribution.
- getVariance() -
Method in class umontreal.iro.lecuyer.probdist.WatsonUDist
-
- getVariance(int) -
Static method in class umontreal.iro.lecuyer.probdist.WatsonUDist
- Returns the variance of the Watson U distribution with
parameter n.
- getVariance() -
Method in class umontreal.iro.lecuyer.probdist.WeibullDist
-
- getVariance(double, double, double) -
Static method in class umontreal.iro.lecuyer.probdist.WeibullDist
- Computes and returns the variance
of the Weibull distribution with parameters α, λ and δ.
- getVarianceDirection() -
Method in class org.apache.commons.math.stat.descriptive.moment.SemiVariance
- Returns the varianceDirection property.
- getVarianceGammaProcess() -
Method in class umontreal.iro.lecuyer.stochprocess.GeometricVarianceGammaProcess
- Returns a reference to the variance gamma process X defined
in the constructor.
- getVarianceImpl() -
Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
- Returns the currently configured variance implementation.
- getVarianceImpl() -
Method in class org.apache.commons.math.stat.descriptive.SummaryStatistics
- Returns the currently configured variance implementation
- getVarianceImpl() -
Method in class org.apache.commons.math.stat.descriptive.SynchronizedSummaryStatistics
- Returns the currently configured variance implementation
- getVarianceMax() -
Method in class jhpro.stat.EEcentricity
- Get variance alone the major axis (longest component)
- getVarianceMin() -
Method in class jhpro.stat.EEcentricity
- Get variance alone the minor (shortest component)
- getVarimaxIterations() -
Method in class flanagan.analysis.PCA
-
- getVarimaxOption() -
Method in class flanagan.analysis.PCA
-
- getVars() -
Method in class jhplot.FND
- Return all variables
- getVarString() -
Method in class jhplot.FND
- Get arguments of the function (independent variables).
- getVersion() -
Method in class jhplot.io.EFile
- Get version of the input file.
- getVersion() -
Method in class jhplot.io.FileRoot
- Get ROOT version
- getVersion() -
Method in class jhplot.io.PFile
- Get version of the input file.
- getVersion() -
Static method in class jhplot.JHPlot
- Get version information
- getVT() -
Method in interface org.apache.commons.math.linear.EigenDecomposition
- Returns the transpose of the matrix V of the decomposition.
- getVT() -
Method in class org.apache.commons.math.linear.EigenDecompositionImpl
- Returns the transpose of the matrix V of the decomposition.
- getVT() -
Method in interface org.apache.commons.math.linear.SingularValueDecomposition
- Returns the transpose of the matrix V of the decomposition.
- getVT() -
Method in class org.apache.commons.math.linear.SingularValueDecompositionImpl
- Returns the transpose of the matrix V of the decomposition.
- getWeight() -
Method in class cern.jet.random.sampling.WeightedRandomSampler
- Not yet commented.
- getWeight() -
Method in class cern.jet.random.tdouble.sampling.WeightedDoubleRandomSampler
-
- getWeight() -
Method in class cern.jet.random.tfloat.sampling.WeightedFloatRandomSampler
-
- getWeight() -
Method in class org.apache.commons.math.estimation.WeightedMeasurement
- Deprecated. Get the weight of the measurement in the least squares problem
- getWeight() -
Method in class org.apache.commons.math.optimization.fitting.WeightedObservedPoint
- Get the weight of the measurement in the fitting process.
- getWeightedResiduals() -
Method in class flanagan.analysis.Regression
-
- getWeightingOption() -
Method in class flanagan.analysis.ProbabilityPlot
-
- getWeights() -
Method in class flanagan.math.FourierTransform
-
- getWeights() -
Method in class umontreal.iro.lecuyer.functionfit.SmoothingCubicSpline
- Returns the weights of the points.
- getWhoAm() -
Method in class jhplot.shapes.HShape
- Primitive type
- getWholeFormat() -
Method in class org.apache.commons.math.fraction.ProperBigFractionFormat
- Access the whole format.
- getWholeFormat() -
Method in class org.apache.commons.math.fraction.ProperFractionFormat
- Access the whole format.
- getWidth() -
Method in class jhplot.jadraw.JaObject
- Returns the width of this object.
- getWidth() -
Method in class jhplot.v3d.Model3d
-
- getWindowOption() -
Method in class flanagan.math.FourierTransform
-
- getWindowSize() -
Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
- Returns the maximum number of values that can be stored in the
dataset, or INFINITE_WINDOW (-1) if there is no limit.
- getWindowSize() -
Method in class org.apache.commons.math.stat.descriptive.SynchronizedDescriptiveStatistics
- Returns the maximum number of values that can be stored in the
dataset, or INFINITE_WINDOW (-1) if there is no limit.
- getX(int) -
Method in class jhplot.F1D
- Get value in X-axis
- getX(int) -
Method in class jhplot.FND
- Get value in X-axis
- getX() -
Method in class jhplot.HKey
- Returns the X position of the text.
- getX() -
Method in class jhplot.HLabel
- Returns the X position of the text.
- getX() -
Method in class jhplot.HLabelEq
- Returns the X position of the text.
- getX() -
Method in class jhplot.HMLabel
- Returns the X position of the text.
- getX() -
Method in class jhplot.jadraw.JaObject
- Returns the x coordinate of this object.
- getX(int) -
Method in class jhplot.P1D
- Return a specific X-value.
- getX(int) -
Method in class jhplot.P2D
- Return a specific X-value.
- getX(int) -
Method in class jhplot.P3D
- Return a specific X-value.
- getX() -
Method in class jhplot.v3d.Vector3d
-
- getX() -
Method in class org.apache.commons.math.geometry.Vector3D
- Get the abscissa of the vector.
- getX() -
Method in class org.apache.commons.math.optimization.fitting.WeightedObservedPoint
- Get the abscissa of the point.
- getX(int, int) -
Method in class umontreal.iro.lecuyer.charts.CustomHistogramDataset
- Returns the X value for a bin.
- getX(int, int) -
Method in class umontreal.iro.lecuyer.charts.SSJXYSeriesCollection
- Returns the x-value at the specified index in the specified series.
- getX() -
Method in class umontreal.iro.lecuyer.functionfit.BSpline
- Returns the Xi coordinates for this spline.
- getX() -
Method in class umontreal.iro.lecuyer.functionfit.LeastSquares
- Returns the x coordinates of the fitted points.
- getX() -
Method in class umontreal.iro.lecuyer.functionfit.PolInterp
- Returns the x coordinates of the interpolated points.
- getX() -
Method in class umontreal.iro.lecuyer.functionfit.SmoothingCubicSpline
- Returns the xi coordinates for this spline.
- getX() -
Method in class umontreal.iro.lecuyer.functions.PiecewiseConstantFunction
- Returns the X coordinates of the function.
- getX0() -
Method in class umontreal.iro.lecuyer.stochprocess.StochasticProcess
- Returns the initial value X(t0) for this process.
- getX1() -
Method in class jhplot.jadraw.JaArcObject
- Returns the x coordinate of the first click point of this arc.
- getX1() -
Method in class jhplot.jadraw.JaVertexT5
- Returns the x coordinate of the first click point of this vertex.
- getX2() -
Method in class jhplot.jadraw.JaArcObject
- Returns the x coordinate of the second click point of this arc.
- getX2() -
Method in class jhplot.jadraw.JaVertexT5
- Returns the x coordinate of the second click point of this vertex.
- getX3() -
Method in class jhplot.jadraw.JaVertexT5
- Returns the x coordinate of the third click point of this vertex.
- getXAutoRange() -
Method in class jhplot.SPlot
- Get the range for X values of the data points registered so far.
- getXAxis() -
Method in class umontreal.iro.lecuyer.charts.MultipleDatasetChart
- Returns the chart's domain axis (x-axis) object.
- getXAxis() -
Method in class umontreal.iro.lecuyer.charts.XYChart
- Returns the chart's domain axis (x-axis) object.
- getXBar() -
Method in class jhplot.stat.LinReg
- Get average x
- getXBar() -
Method in class jhplot.stat.LinRegWeighted
- Get average x
- getXc() -
Method in class umontreal.iro.lecuyer.probdist.InverseDistFromDensity
- Returns the xc given in the constructor.
- getXc() -
Method in class umontreal.iro.lecuyer.randvar.InverseFromDensityGen
- Returns the xc given in the constructor.
- getXdata() -
Method in class flanagan.analysis.Regression
-
- getXi() -
Method in class umontreal.iro.lecuyer.probdist.JohnsonSBDist
- Returns the value of ξ for this object.
- getXi() -
Method in class umontreal.iro.lecuyer.probdist.JohnsonSUDist
- Returns the value of ξ for this object.
- getXi() -
Method in class umontreal.iro.lecuyer.randvar.JohnsonSBGen
- Returns the ξ associated with this object.
- getXi() -
Method in class umontreal.iro.lecuyer.randvar.JohnsonSUGen
- Returns the ξ associated with this object.
- getXinf() -
Method in class umontreal.iro.lecuyer.probdist.ContinuousDistribution
- Returns xa such that the probability density is 0 everywhere
outside the interval
[xa, xb].
- getXinf() -
Method in class umontreal.iro.lecuyer.probdist.DiscreteDistribution
- Returns the lower limit xa of the support of the distribution.
- getXinf() -
Method in class umontreal.iro.lecuyer.probdist.DiscreteDistributionInt
- Returns the lower limit xa of the support of the probability
mass function.
- getXLabel() -
Method in class jhplot.SPlot
- Get the label for the X (horizontal) axis, or null if none has been set.
- getXleft(int) -
Method in class jhplot.P1D
- Return a specific left error on X-value.
- getXleftSys(int) -
Method in class jhplot.P1D
- Return a specific left error on X-value (systematic error).
- getXLog() -
Method in class jhplot.SPlot
- Return whether the X axis is drawn with a logarithmic scale.
- getXmax() -
Method in class flanagan.interpolation.BiCubicSpline
-
- getXmax() -
Method in class flanagan.interpolation.BiCubicSplineFirstDerivative
-
- getXmax() -
Method in class flanagan.interpolation.BiCubicSplinePartialDerivative
-
- getXmax() -
Method in class flanagan.interpolation.CubicSpline
-
- getXmax() -
Method in class flanagan.interpolation.PolyCubicSpline
-
- getXmax() -
Method in class flanagan.interpolation.QuadriCubicSpline
-
- getXmax() -
Method in class flanagan.interpolation.TriCubicSpline
-
- getXmin() -
Method in class flanagan.interpolation.BiCubicSpline
-
- getXmin() -
Method in class flanagan.interpolation.BiCubicSplineFirstDerivative
-
- getXmin() -
Method in class flanagan.interpolation.BiCubicSplinePartialDerivative
-
- getXmin() -
Method in class flanagan.interpolation.CubicSpline
-
- getXmin() -
Method in class flanagan.interpolation.PolyCubicSpline
-
- getXmin() -
Method in class flanagan.interpolation.QuadriCubicSpline
-
- getXmin() -
Method in class flanagan.interpolation.TriCubicSpline
-
- getXndc() -
Method in class jhplot.jadraw.JaObject
- Returns the NDC x coordinate of this object.
- getXRange() -
Method in class jhplot.SPlot
- Get the X range.
- getXright(int) -
Method in class jhplot.P1D
- Return a specific right error on X-value.
- getXrightSys(int) -
Method in class jhplot.P1D
- Return a specific right error on X-value (systematic error).
- getXSumSquares() -
Method in class org.apache.commons.math.stat.regression.SimpleRegression
- Returns the sum of squared deviations of the x values about their mean.
- getXsup() -
Method in class umontreal.iro.lecuyer.probdist.ContinuousDistribution
- Returns xb such that the probability density is 0 everywhere
outside the interval
[xa, xb].
- getXsup() -
Method in class umontreal.iro.lecuyer.probdist.DiscreteDistribution
- Returns the upper limit xb of the support of the distribution.
- getXsup() -
Method in class umontreal.iro.lecuyer.probdist.DiscreteDistributionInt
- Returns the upper limit xb of the support of the probability
mass function.
- getXTicks() -
Method in class jhplot.SPlot
- Get the X ticks that have been specified, or null if none.
- getXuser() -
Method in class jhplot.jadraw.JaObject
- Returns the USER x coordinate of this object.
- getXYCoord(int, int, int, int) -
Method in class jhplot.jadraw.JaBox
- Get coordinates of the box
- getY(int) -
Method in class jhplot.F1D
- Get value in Y-axis
- getY(int) -
Method in class jhplot.FND
- Get value in Y-axis
- getY() -
Method in class jhplot.HKey
- Returns the Y position of the text.
- getY() -
Method in class jhplot.HLabel
- Returns the Y position of the text.
- getY() -
Method in class jhplot.HLabelEq
- Returns the Y position of the text.
- getY() -
Method in class jhplot.HMLabel
- Returns the Y position of the text.
- getY() -
Method in class jhplot.jadraw.JaObject
- Returns the y coordinate of this object.
- getY(int) -
Method in class jhplot.P1D
- Return a specific Y-value.
- getY(int) -
Method in class jhplot.P2D
- Return a specific Y-value.
- getY(int) -
Method in class jhplot.P3D
- Return a specific Y-value.
- getY() -
Method in class jhplot.v3d.Vector3d
-
- getY() -
Method in class org.apache.commons.math.geometry.Vector3D
- Get the ordinate of the vector.
- getY() -
Method in class org.apache.commons.math.optimization.fitting.WeightedObservedPoint
- Get the observed value of the function at x.
- getY(int, int) -
Method in class umontreal.iro.lecuyer.charts.CustomHistogramDataset
- Returns the y-value for a bin (calculated to take into account the
histogram type).
- getY(int, int) -
Method in class umontreal.iro.lecuyer.charts.SSJXYSeriesCollection
- Returns the y-value at the specified index in the specified series.
- getY() -
Method in class umontreal.iro.lecuyer.functionfit.BSpline
- Returns the Yi coordinates for this spline.
- getY() -
Method in class umontreal.iro.lecuyer.functionfit.LeastSquares
- Returns the y coordinates of the fitted points.
- getY() -
Method in class umontreal.iro.lecuyer.functionfit.PolInterp
- Returns the y coordinates of the interpolated points.
- getY() -
Method in class umontreal.iro.lecuyer.functionfit.SmoothingCubicSpline
- Returns the yi coordinates for this spline.
- getY() -
Method in class umontreal.iro.lecuyer.functions.PiecewiseConstantFunction
- Returns the Y coordinates of
the function.
- getY1() -
Method in class jhplot.jadraw.JaArcObject
- Returns the y coordinate of the first click point of this arc.
- getY1() -
Method in class jhplot.jadraw.JaVertexT5
- Returns the y coordinate of the first click point of this vertex.
- getY2() -
Method in class jhplot.jadraw.JaArcObject
- Returns the y coordinate of the second click point of this arc.
- getY2() -
Method in class jhplot.jadraw.JaVertexT5
- Returns the y coordinate of the second click point of this vertex.
- getY3() -
Method in class jhplot.jadraw.JaVertexT5
- Returns the y coordinate of the third click point of this vertex.
- getYAutoRange() -
Method in class jhplot.SPlot
- Get the range for Y values of the data points registered so far.
- getYAxis() -
Method in class umontreal.iro.lecuyer.charts.CategoryChart
- Returns the chart's range axis (y-axis) object.
- getYAxis() -
Method in class umontreal.iro.lecuyer.charts.MultipleDatasetChart
- Returns the chart's range axis (y-axis) object.
- getYAxis() -
Method in class umontreal.iro.lecuyer.charts.XYChart
- Returns the chart's range axis (y-axis) object.
- getYBar() -
Method in class jhplot.stat.LinReg
- Get average Y
- getYBar() -
Method in class jhplot.stat.LinRegWeighted
- Get average Y
- getYcalc() -
Method in class flanagan.analysis.Regression
-
- getYdata() -
Method in class flanagan.analysis.Regression
-
- getYear() -
Method in class flanagan.math.TimeAndDate
-
- getYLabel() -
Method in class jhplot.SPlot
- Get the label for the Y (vertical) axis, or null if none has been set.
- getYLog() -
Method in class jhplot.SPlot
- Return whether the Y axis is drawn with a logarithmic scale.
- getYlower(int) -
Method in class jhplot.P1D
- Return a specific lower error on Y-value.
- getYlowerSys(int) -
Method in class jhplot.P1D
- Return a specific total lower error on Y-value.
- getYndc() -
Method in class jhplot.jadraw.JaObject
- Returns the NDC y coordinate of this object.
- getYRange() -
Method in class jhplot.SPlot
- Get the Y range.
- getYscale() -
Method in class flanagan.analysis.Regression
-
- getYscaleOption() -
Method in class flanagan.analysis.Regression
-
- getYTicks() -
Method in class jhplot.SPlot
- Get the Y ticks that have been specified, or null if none.
- getYupper(int) -
Method in class jhplot.P1D
- Return a specific upper error on Y-value.
- getYupperSys(int) -
Method in class jhplot.P1D
- Return a specific systematical upper error on Y-value.
- getYuser() -
Method in class jhplot.jadraw.JaObject
- Returns the USER y coordinate of this object.
- getZ(int) -
Method in class jhplot.P2D
- Return a specific Z-value.
- getZ(int) -
Method in class jhplot.P3D
- Return a specific Z-value.
- getZ() -
Method in class jhplot.v3d.Vector3d
-
- getZ() -
Method in class org.apache.commons.math.geometry.Vector3D
- Get the height of the vector.
- getZero() -
Method in class org.apache.commons.math.complex.ComplexField
- Get the additive identity of the field.
- getZero() -
Method in class org.apache.commons.math.dfp.Dfp
- Get the constant 0.
- getZero() -
Method in class org.apache.commons.math.dfp.DfpField
- Get the constant 0.
- getZero() -
Method in interface org.apache.commons.math.Field
- Get the additive identity of the field.
- getZero() -
Method in class org.apache.commons.math.fraction.BigFractionField
- Get the additive identity of the field.
- getZero() -
Method in class org.apache.commons.math.fraction.FractionField
- Get the additive identity of the field.
- getZero() -
Method in class org.apache.commons.math.util.BigRealField
- Get the additive identity of the field.
- getZeroOverZeroValue() -
Method in class umontreal.iro.lecuyer.util.RatioFunction
- Returns the value returned by
evaluate
in the
case where the 0/0 function is calculated.
- GeV -
Static variable in class cern.clhep.Units
-
- GHFrame - Class in jhplot
- Create main Frame with several plots.
- GHFrame(String, int, int, int, int, boolean) -
Constructor for class jhplot.GHFrame
- Create main frame window
- GHFrame(String, int, int) -
Constructor for class jhplot.GHFrame
- Construct a GHFrame with a single plot/graph.
- GHFrame(String, int, int, boolean) -
Constructor for class jhplot.GHFrame
- Construct a GHFrame canvas with a single plot/graph.
- GHFrame(String, int, int, int, int) -
Constructor for class jhplot.GHFrame
- Construct a GHFrame canvas with plots/graphs.
- GHFrame(String) -
Constructor for class jhplot.GHFrame
- Construct a GHFrame canvas with a plot with the default parameters 600 by
400, and 10% space for the global title
- GHFrame() -
Constructor for class jhplot.GHFrame
- Construct a GHFrame canvas with a plot with the default parameters 600 by
400, and 10% space for the global title "Default".
- GHMargin - Class in jhplot
- Panels with global margin.
- GHMargin(GHPanel, String) -
Constructor for class jhplot.GHMargin
- Main class to create global margin
- GHPanel - Class in jhplot
- Class to build the global panel with graphics.
- GHPanel(int, int) -
Constructor for class jhplot.GHPanel
- Create a panel with graphics.
- gigaelectronvolt -
Static variable in class cern.clhep.Units
-
- GillIntegrator - Class in org.apache.commons.math.ode.nonstiff
- This class implements the Gill fourth order Runge-Kutta
integrator for Ordinary Differential Equations .
- GillIntegrator(double) -
Constructor for class org.apache.commons.math.ode.nonstiff.GillIntegrator
- Simple constructor.
- GlArc(float, float, float, float, float, float) -
Static method in class jhplot.jadraw.Diagram
-
- GLine(float, float) -
Static method in class jhplot.jadraw.Diagram
- A g-line for ghost particles.
- GlLine(float, float) -
Static method in class jhplot.jadraw.Diagram
- Get a gluon line object
- GlLoop(float, float) -
Static method in class jhplot.jadraw.Diagram
- Get a gluon loop object
- GlobalCPUTimeChrono - Class in umontreal.iro.lecuyer.util
- Extends the
AbstractChrono
class to compute the global CPU time used
by the Java Virtual Machine. - GlobalCPUTimeChrono() -
Constructor for class umontreal.iro.lecuyer.util.GlobalCPUTimeChrono
- Constructs a Chrono object and initializes it to zero.
- GLoop(float, float) -
Static method in class jhplot.jadraw.Diagram
- Get a g-loop object
- GLSMultipleLinearRegression - Class in org.apache.commons.math.stat.regression
- The GLS implementation of the multiple linear regression.
- GLSMultipleLinearRegression() -
Constructor for class org.apache.commons.math.stat.regression.GLSMultipleLinearRegression
-
- GNUPLOT -
Static variable in class umontreal.iro.lecuyer.gof.GofFormat
- Data file format used for plotting functions with Gnuplot.
- GoalType - Enum in org.apache.commons.math.optimization
- Goal type for an optimization problem.
- GofFormat - Class in umontreal.iro.lecuyer.gof
- This class contains methods used to format results of GOF
test statistics, or to apply a series of tests
simultaneously and format the results.
- GofStat - Class in umontreal.iro.lecuyer.gof
- This class provides methods to compute several types of EDF goodness-of-fit
test statistics and to apply certain transformations to a set of
observations.
- GofStat.OutcomeCategoriesChi2 - Class in umontreal.iro.lecuyer.gof
- This class helps managing the partitions of possible outcomes
into categories for applying chi-square tests.
- GofStat.OutcomeCategoriesChi2(double[]) -
Constructor for class umontreal.iro.lecuyer.gof.GofStat.OutcomeCategoriesChi2
- Constructs an OutcomeCategoriesChi2 object
using the array nbExp for the number of expected observations in
each category.
- GofStat.OutcomeCategoriesChi2(double[], int, int) -
Constructor for class umontreal.iro.lecuyer.gof.GofStat.OutcomeCategoriesChi2
- Constructs an OutcomeCategoriesChi2 object using the
given nbExp expected observations array.
- GofStat.OutcomeCategoriesChi2(double[], int[], int, int, int) -
Constructor for class umontreal.iro.lecuyer.gof.GofStat.OutcomeCategoriesChi2
- Constructs an OutcomeCategoriesChi2 object.
- goodFriday() -
Method in class flanagan.math.TimeAndDate
-
- goodFriday(int) -
Method in class flanagan.math.TimeAndDate
-
- gradient(double[]) -
Method in class hep.aida.ref.fitter.InternalFitFunction
-
- gradient(double[]) -
Method in class hep.aida.ref.function.AbstractDevModelFunction
-
- gradient(double[]) -
Method in class hep.aida.ref.function.AbstractIFunction
-
- gradient(double[]) -
Method in class hep.aida.ref.function.BaseModelFunction
-
- gradient(double[]) -
Method in class hep.aida.ref.function.ExponentialCoreNorm
-
- gradient(double[]) -
Method in class hep.aida.ref.function.ExponentialCoreNotNorm
-
- gradient(double[]) -
Method in class hep.aida.ref.function.FunctionCore
-
- gradient(double[]) -
Method in class hep.aida.ref.function.GaussianCore2DNorm
-
- gradient(double[]) -
Method in class hep.aida.ref.function.GaussianCore2DNotNorm
-
- gradient(double[]) -
Method in class hep.aida.ref.function.GaussianCoreNorm
-
- gradient(double[]) -
Method in class hep.aida.ref.function.GaussianCoreNotNorm
-
- gradient(double[]) -
Method in class hep.aida.ref.function.IFunctionCoreNotNorm
-
- gradient(double[]) -
Method in class hep.aida.ref.function.JELFunctionCore
-
- gradient(double[]) -
Method in class hep.aida.ref.function.LorentzianCoreNotNorm
-
- gradient(double[]) -
Method in class hep.aida.ref.function.MoyalCoreNotNorm
-
- gradient(double[]) -
Method in class hep.aida.ref.function.PolynomialCoreNorm
-
- gradient(double[]) -
Method in class hep.aida.ref.function.PolynomialCoreNotNorm
-
- gradient(double[]) -
Method in class hep.aida.ref.function.SumOfFunctions
-
- gradient() -
Method in interface org.apache.commons.math.analysis.DifferentiableMultivariateRealFunction
- Returns the gradient function.
- gradient(double, double[]) -
Method in class org.apache.commons.math.optimization.fitting.ParametricGaussianFunction
- Computes the gradient vector for a four variable version of the function
where the parameters, a, b, c, and d,
are considered the variables, not x.
- gradient(double, double[]) -
Method in interface org.apache.commons.math.optimization.fitting.ParametricRealFunction
- Compute the gradient of the function with respect to its parameters.
- GraggBulirschStoerIntegrator - Class in org.apache.commons.math.ode.nonstiff
- This class implements a Gragg-Bulirsch-Stoer integrator for
Ordinary Differential Equations.
- GraggBulirschStoerIntegrator(double, double, double, double) -
Constructor for class org.apache.commons.math.ode.nonstiff.GraggBulirschStoerIntegrator
- Simple constructor.
- GraggBulirschStoerIntegrator(double, double, double[], double[]) -
Constructor for class org.apache.commons.math.ode.nonstiff.GraggBulirschStoerIntegrator
- Simple constructor.
- gram -
Static variable in class cern.clhep.Units
-
- gramToOunce(double) -
Static method in class flanagan.math.Conv
-
- gramToOunce(double) -
Static method in class flanagan.math.Fmath
-
- graph(Graphics) -
Method in class flanagan.math.FourierTransform
-
- graphDistUnif(DoubleArrayList, String) -
Static method in class umontreal.iro.lecuyer.gof.GofFormat
- Formats data to plot the empirical distribution of
U(1),..., U(N), which are assumed to be in data[0...N-1],
and to compare it with the uniform distribution.
- graphSoft -
Static variable in class umontreal.iro.lecuyer.gof.GofFormat
- Environment variable that selects the type of software to be
used for plotting the graphs of functions.
- gray -
Static variable in class cern.clhep.Units
-
- greater(DoubleMatrix2D, double) -
Static method in class cern.colt.matrix.doublealgo.Transform
- Deprecated. A[row,col] = A[row,col] > s ? 1 : 0.
- greater(DoubleMatrix2D, DoubleMatrix2D) -
Static method in class cern.colt.matrix.doublealgo.Transform
- Deprecated. A[row,col] = A[row,col] > B[row,col] ? 1 : 0.
- greater -
Static variable in class cern.jet.math.Functions
- Function that returns a > b ? 1 : 0.
- greater(double) -
Static method in class cern.jet.math.Functions
- Constructs a function that returns a > b ? 1 : 0.
- greater -
Static variable in class cern.jet.math.tdouble.DoubleFunctions
- Function that returns a > b ? 1 : 0.
- greater(double) -
Static method in class cern.jet.math.tdouble.DoubleFunctions
- Constructs a function that returns a > b ? 1 : 0.
- greater -
Static variable in class cern.jet.math.tfloat.FloatFunctions
- Function that returns a > b ? 1 : 0.
- greater(float) -
Static method in class cern.jet.math.tfloat.FloatFunctions
- Constructs a function that returns a > b ? 1 : 0.
- greaterThan(Dfp) -
Method in class org.apache.commons.math.dfp.Dfp
- Check if instance is greater than x.
- Grid - Class in hep.aida.ref.function
-
- Grid(IModelFunction) -
Constructor for class hep.aida.ref.function.Grid
-
- guess() -
Method in class org.apache.commons.math.optimization.fitting.GaussianParametersGuesser
- Guesses the parameters based on the observed points.
- guess() -
Method in class org.apache.commons.math.optimization.fitting.HarmonicCoefficientsGuesser
- Estimate a first guess of the coefficients.
- guessParametersErrors(EstimationProblem) -
Method in class org.apache.commons.math.estimation.AbstractEstimator
- Deprecated. Guess the errors in unbound estimated parameters.
- guessParametersErrors(EstimationProblem) -
Method in interface org.apache.commons.math.estimation.Estimator
- Deprecated. Guess the errors in estimated parameters.
- guessParametersErrors() -
Method in class org.apache.commons.math.optimization.general.AbstractLeastSquaresOptimizer
- Guess the errors in optimized parameters.
- GumbelDist - Class in umontreal.iro.lecuyer.probdist
- Extends the class
ContinuousDistribution
for
the Gumbel distribution, with location parameter
δ and scale parameter
β≠ 0. - GumbelDist() -
Constructor for class umontreal.iro.lecuyer.probdist.GumbelDist
- Constructor for the standard
Gumbel distribution with parameters β = 1 and δ = 0.
- GumbelDist(double, double) -
Constructor for class umontreal.iro.lecuyer.probdist.GumbelDist
- Constructs a GumbelDist object with parameters
β = beta and δ = delta.
- GumbelGen - Class in umontreal.iro.lecuyer.randvar
- This class implements methods for generating random variates from the
Gumbel distribution.
- GumbelGen(RandomStream) -
Constructor for class umontreal.iro.lecuyer.randvar.GumbelGen
- Creates a Gumbel random number generator with
β = 1 and
δ = 0 using stream s.
- GumbelGen(RandomStream, double, double) -
Constructor for class umontreal.iro.lecuyer.randvar.GumbelGen
- Creates a Gumbel random number generator with parameters
β = beta and δ = delta using stream s.
- GumbelGen(RandomStream, GumbelDist) -
Constructor for class umontreal.iro.lecuyer.randvar.GumbelGen
- Creates a new generator for the Gumbel distribution dist
and stream s.
- gumbelMax() -
Method in class flanagan.analysis.Regression
-
- gumbelMax(double, double, double) -
Static method in class flanagan.analysis.Stat
-
- gumbelMaxCDF(double, double, double) -
Static method in class flanagan.analysis.Stat
-
- gumbelMaxCDF(double, double, double, double) -
Static method in class flanagan.analysis.Stat
-
- gumbelMaxCorrelationCoefficient() -
Method in class flanagan.analysis.ProbabilityPlot
-
- gumbelMaxGradient() -
Method in class flanagan.analysis.ProbabilityPlot
-
- gumbelMaxGradientError() -
Method in class flanagan.analysis.ProbabilityPlot
-
- gumbelMaxIntercept() -
Method in class flanagan.analysis.ProbabilityPlot
-
- gumbelMaxInterceptError() -
Method in class flanagan.analysis.ProbabilityPlot
-
- gumbelMaxInverseCDF(double, double, double) -
Static method in class flanagan.analysis.Stat
-
- gumbelMaxMean(double, double) -
Static method in class flanagan.analysis.Stat
-
- gumbelMaxMedian(double, double) -
Static method in class flanagan.analysis.Stat
-
- gumbelMaxMode(double, double) -
Static method in class flanagan.analysis.Stat
-
- gumbelMaxMu() -
Method in class flanagan.analysis.ProbabilityPlot
-
- gumbelMaxMuError() -
Method in class flanagan.analysis.ProbabilityPlot
-
- gumbelMaxOnePar() -
Method in class flanagan.analysis.Regression
-
- gumbelMaxOneParPlot() -
Method in class flanagan.analysis.Regression
-
- gumbelMaxOrderStatisticMedians() -
Method in class flanagan.analysis.ProbabilityPlot
-
- gumbelMaxOrderStatisticMedians(double, double, int) -
Static method in class flanagan.analysis.Stat
-
- gumbelMaxPDF(double, double, double) -
Static method in class flanagan.analysis.Stat
-
- gumbelMaxPlot() -
Method in class flanagan.analysis.Regression
-
- gumbelMaxProb(double, double, double) -
Static method in class flanagan.analysis.Stat
-
- gumbelMaxProb(double, double, double, double) -
Static method in class flanagan.analysis.Stat
-
- gumbelMaxProbabilityPlot() -
Method in class flanagan.analysis.ProbabilityPlot
-
- gumbelMaxRand(double, double, int) -
Static method in class flanagan.analysis.Stat
-
- gumbelMaxRand(double, double, int, long) -
Static method in class flanagan.analysis.Stat
-
- gumbelMaxSigma() -
Method in class flanagan.analysis.ProbabilityPlot
-
- gumbelMaxSigmaError() -
Method in class flanagan.analysis.ProbabilityPlot
-
- gumbelMaxStandard() -
Method in class flanagan.analysis.Regression
-
- gumbelMaxStandardDeviation(double) -
Static method in class flanagan.analysis.Stat
-
- gumbelMaxStandardPlot() -
Method in class flanagan.analysis.Regression
-
- gumbelMaxStandDev(double) -
Static method in class flanagan.analysis.Stat
-
- gumbelMaxSumOfSquares() -
Method in class flanagan.analysis.ProbabilityPlot
-
- gumbelMin() -
Method in class flanagan.analysis.Regression
-
- gumbelMin(double, double, double) -
Static method in class flanagan.analysis.Stat
-
- gumbelMinCDF(double, double, double, double) -
Static method in class flanagan.analysis.Stat
-
- gumbelMinCorrelationCoefficient() -
Method in class flanagan.analysis.ProbabilityPlot
-
- gumbelMinGradient() -
Method in class flanagan.analysis.ProbabilityPlot
-
- gumbelMinGradientError() -
Method in class flanagan.analysis.ProbabilityPlot
-
- gumbelMinIntercept() -
Method in class flanagan.analysis.ProbabilityPlot
-
- gumbelMinInterceptError() -
Method in class flanagan.analysis.ProbabilityPlot
-
- gumbelMinInverseCDF(double, double, double) -
Static method in class flanagan.analysis.Stat
-
- gumbelMinMean(double, double) -
Static method in class flanagan.analysis.Stat
-
- gumbelMinMedian(double, double) -
Static method in class flanagan.analysis.Stat
-
- gumbelMinMode(double, double) -
Static method in class flanagan.analysis.Stat
-
- gumbelMinMu() -
Method in class flanagan.analysis.ProbabilityPlot
-
- gumbelMinMuError() -
Method in class flanagan.analysis.ProbabilityPlot
-
- gumbelMinOnePar() -
Method in class flanagan.analysis.Regression
-
- gumbelMinOneParPlot() -
Method in class flanagan.analysis.Regression
-
- gumbelMinOrderStatisticMedians() -
Method in class flanagan.analysis.ProbabilityPlot
-
- gumbelMinOrderStatisticMedians(double, double, int) -
Static method in class flanagan.analysis.Stat
-
- gumbelMinPDF(double, double, double) -
Static method in class flanagan.analysis.Stat
-
- gumbelMinPlot() -
Method in class flanagan.analysis.Regression
-
- gumbelMinProb(double, double, double) -
Static method in class flanagan.analysis.Stat
-
- gumbelMinProb(double, double, double, double) -
Static method in class flanagan.analysis.Stat
-
- gumbelMinProbabilityPlot() -
Method in class flanagan.analysis.ProbabilityPlot
-
- gumbelMinProbCDF(double, double, double) -
Static method in class flanagan.analysis.Stat
-
- gumbelMinRand(double, double, int) -
Static method in class flanagan.analysis.Stat
-
- gumbelMinRand(double, double, int, long) -
Static method in class flanagan.analysis.Stat
-
- gumbelMinSigma() -
Method in class flanagan.analysis.ProbabilityPlot
-
- gumbelMinSigmaError() -
Method in class flanagan.analysis.ProbabilityPlot
-
- gumbelMinStandard() -
Method in class flanagan.analysis.Regression
-
- gumbelMinStandardDeviation(double) -
Static method in class flanagan.analysis.Stat
-
- gumbelMinStandardPlot() -
Method in class flanagan.analysis.Regression
-
- gumbelMinStandDev(double) -
Static method in class flanagan.analysis.Stat
-
- gumbelMinSumOfSquares() -
Method in class flanagan.analysis.ProbabilityPlot
-
ContinuousDistribution
for the half-normal
distribution with parameters μ and
σ > 0.f (t) = a cos (ω t + φ)
.resetStartProcess
.
EventList
using the doubly-linked
indexed list of Henriksen (see also).TallyStore
object.
StatisticalSummary
instances, under the
assumption of equal subpopulation variances.
StatisticalSummary
instances, under the
assumption of equal subpopulation variances.
sample1
and sample2
are drawn from populations with the same mean,
with significance level alpha
, assuming that the
subpopulation variances are equal.
sample1
and sample2
are drawn from populations with the same mean,
with significance level alpha
, assuming that the
subpopulation variances are equal.
text
with html
masked expressions.
ContinuousDistribution
for
the Hyperbolic Secant distribution with location
parameter μ and scale parameter
σ > 0.DiscreteDistributionInt
for
the hypergeometric distribution with
k elements chosen among l, m being
of one type, and l - m of the other.HypergeometricDistribution
.x
and y
- sqrt(x2 +y2)iBinomialMatrixScramble
except that the diagonal
elements of each matrix
Mj are chosen as in
leftMatrixScrambleFaurePermut
.
iBinomialMatrixScrambleFaurePermut
except that the
elements under the diagonal are also
chosen from the same restricted set as the diagonal elements.
iBinomialMatrixScrambleFaurePermut
except that all the
off-diagonal elements are 0.
{0, 1, ..., n}
RandomMultivariateGen
for a vector of independent identically distributed
(i.i.d.) random variables.AbstractStorelessUnivariateStatistic.increment(double)
in a loop over
the input array.
AbstractStorelessUnivariateStatistic.increment(double)
in a loop over
the specified portion of the input array.
permutedData
when applied to
originalData
.
init
(byte[], int).
init
(byte[], int).
init
(byte[], int).
init
(byte[], int).
init
(byte[], int).
init
followed by update
(x).
init
, but also chooses evlist as the
event list to be used.
init
, but also chooses evlist as the
event list to be used.
SplayTree
algorithm
as EventList
.
EventList
.
init
on each element.
setStatCollecting
(true) and makes an update for the
probe on the list size.
int
elements; implemented with arrays.int
elements; implemented with arrays.UnivariateRealIntegrator.integrate(UnivariateRealFunction, double, double)
since 2.0
IntegratorException.IntegratorException(Localizable, Object...)
SplineInterpolator
on the resulting fit.
AbstractIntList
to be viewed and treated as a JDK 1.2 AbstractList
.AbstractIntList
to be
viewed and treated as a JDK 1.2 AbstractList
.InvalidMatrixException.InvalidMatrixException(Localizable, Object...)
new LUDecompositionImpl(m)
.getSolver()
.getInverse()
p
.
p
.
p
.
p
.
p
.
p
.
p
.
p
.
p
.
p
.
p
.
p
.
p
.
inverseF
(alpha, beta, 0, 1, d, u).
inverseF
(alpha, 1, d, u).
NormalDist.inverseF01
.
inverseF
(0, 1, u).
inverseF
(0.0, 1.0, u).
ContinuousDistribution
for
the inverse gamma distribution with shape parameter
α > 0 and scale parameter β > 0.ContinuousDistribution
for
the inverse Gaussian distribution with location parameter
μ > 0 and scale parameter
λ > 0.InverseGaussianDist
.InverseGaussianProcess
.ComposableFunction
.
true
if the matrix is in array format, else
false
true
if the vector is in array format, else
false
true
if the matrix stores complex numbers, else
false
true
if the vector stores complex numbers, else
false
true
if the matrix is in coordinate format, else
false
true
if the vector is in coordinate format, else
false
true
if the matrix is in array format, else
false
true
if the vector is in array format, else
false
true
if the matrix form is general, else
false
true
if the matrix is Hermitian, else
false
Double.POSITIVE_INFINITY
or
Double.NEGATIVE_INFINITY
) and neither part
is NaN
.
NaN
.
NaN
.
true
if the matrix stores integers, else
false
true
if the vector stores integers, else
false
NaN
.
NaN
.
true
if the matrix does not store any numbers, else
false
true
if the vector does not store any numbers, else
false
true
if the matrix stores real numbers, else
false
true
if the vector stores real numbers, else
false
new LUDecompositionImpl(m)
.getSolver()
.isNonSingular()
true
if the matrix is skew-symmetrical, else
false
true
if the matrix is in coordinate format, else
false
true
if the vector is in coordinate format, else
false
true
if the matrix is square, else
false
true
if the matrix is symmetrical, else
false
iterator
, except that the first coordinate
of the points is i/n, the second coordinate is obtained via
the generating matrix
C0, the next one via
C1,
and so on.
iterator
, except that the first coordinate
of the points is i/n, the second coordinate is obtained via
the generating matrix
C0, the next one via
C1,
and so on.
iterSpacingsTests
, but with the
GofStat.powerRatios
transformation.
GofStat.iterateSpacings
transformation to the
U(0),..., U(N-1), assuming that these observations are in
sortedData, then computes the EDF test statistics and calls
activeTests
after each transformation.
java.util.Random
to implement
RandomGenerator
.ContinuousDistribution
for
the Johnson SB distribution
with shape parameters γ and
δ > 0, location parameter ξ,
and scale parameter λ > 0.ContinuousDistribution
for
the Johnson SU distribution.JohnsonSUDist
(gamma, delta, 0.0, 1.0).
KernelDensityGen
, but with
a rescaling of the empirical distribution so that the variance
of the density used to generate the random variates is equal
to the empirical variance,
as suggested by Silverman.ContinuousDistribution
for the
Kolmogorov-Smirnov distribution with parameter n.KolmogorovSmirnovDist
for the distribution.FDist.kolmogorovSmirnovPlusJumpOne
, assuming that F is the
uniform distribution over [0, 1] and that
U(1),..., U(N) are in sortedData.
ContinuousDistribution
for the
Kolmogorov-Smirnov+ distribution (see).KolmogorovSmirnovPlusDist
but for the case where the distribution function F has a jump of size
a at a given point x0, is zero at the left of x0,
and is continuous at the right of x0.
LCGPointSet
, but implemented differently.Kurtosis
identical
to the original
LaguerreSolver.solve(UnivariateRealFunction, double, double)
or
UnivariateRealSolver.solve(UnivariateRealFunction, double, double, double)
method.
ContinuousDistribution
for
the Laplace distribution.lcm(a,b) = (a / gcd(a,b)) * b
.
lcm(a,b) = (a / gcd(a,b)) * b
.
vectorial
objective functions
to scalar objective functions
when the goal is to minimize them.leftMatrixScramble
except that all the
off-diagonal elements of the
Mj are 0.
leftMatrixScramble
except that the diagonal elements
of each matrix
Mj are chosen from a restricted set of the best
integers as calculated by Faure.
leftMatrixScrambleFaurePermut
except that the
elements under the diagonal are also
chosen from the same restricted set as the diagonal elements.
leftMatrixScrambleFaurePermut
except that all
off-diagonal elements are 0.
RandomStreamBase
using a composite linear feedback
shift register (LFSR) (or Tausworthe) RNG as defined in.RandomStreamBase
using a 64-bit composite linear feedback
shift register (LFSR) (or Tausworthe) RNG as defined in.ListWithStat
, and
uses a linked list as the internal data structure.ListOfTallies
to add support for the computation
of the sample covariance between each pair of elements
in a list, without storing all observations.List
.PointSetRandomization
that performs a left matrix scrambling and adds a random digital
shift.LoessInterpolator
with a bandwidth of LoessInterpolator.DEFAULT_BANDWIDTH
,
LoessInterpolator.DEFAULT_ROBUSTNESS_ITERS
robustness iterations
and an accuracy of {#link #DEFAULT_ACCURACY}.
LoessInterpolator
with given bandwidth and number of robustness iterations.
LoessInterpolator
with given bandwidth, number of robustness iterations and accuracy.
FastMath.log
method wrapped as a ComposableFunction
.
b
of x
.
FastMath.log10
method wrapped as a ComposableFunction
.
FastMath.log1p
method wrapped as a ComposableFunction
.
DiscreteDistributionInt
for
the logarithmic distribution.ContinuousDistribution
for the
logistic distribution.ContinuousDistribution
for the
Log-Logistic distribution with shape parameter
α > 0
and scale parameter β > 0.ContinuousDistribution
for the
lognormal distribution.LognormalDist
class with a constructor accepting the
mean m and the variance v of the distribution as arguments.long
elements; implemented with arrays.long
elements; implemented with arrays.AbstractLongList
to be viewed and treated as a JDK 1.2 AbstractList
.AbstractLongList
to be
viewed and treated as a JDK 1.2 AbstractList
.LUDecomposition
LUDecomposition
, avoiding unnecessary memory allocation and copying.Math.abs(double)
function to each entry.
Math.abs(double)
function to each entry.
Math.abs(double)
function to each entry.
Math.acos(double)
function to each entry.
Math.acos(double)
function to each entry.
Math.acos(double)
function to each entry.
Math.asin(double)
function to each entry.
Math.asin(double)
function to each entry.
Math.asin(double)
function to each entry.
Math.atan(double)
function to each entry.
Math.atan(double)
function to each entry.
Math.atan(double)
function to each entry.
Math.cbrt(double)
function to each entry.
Math.cbrt(double)
function to each entry.
Math.cbrt(double)
function to each entry.
Math.ceil(double)
function to each entry.
Math.ceil(double)
function to each entry.
Math.ceil(double)
function to each entry.
Math.cos(double)
function to each entry.
Math.cosh(double)
function to each entry.
Math.cosh(double)
function to each entry.
Math.cosh(double)
function to each entry.
Math.cos(double)
function to each entry.
Math.cos(double)
function to each entry.
Math.exp(double)
function to each entry.
Math.expm1(double)
function to each entry.
Math.expm1(double)
function to each entry.
Math.expm1(double)
function to each entry.
Math.exp(double)
operation to each entry.
Math.exp(double)
operation to each entry.
Math.floor(double)
function to each entry.
Math.floor(double)
function to each entry.
Math.floor(double)
function to each entry.
Math.log(double)
function to each entry.
Math.log10(double)
function to each entry.
Math.log10(double)
function to each entry.
Math.log10(double)
function to each entry.
Math.log1p(double)
function to each entry.
Math.log1p(double)
function to each entry.
Math.log1p(double)
function to each entry.
Math.log(double)
function to each entry.
Math.log(double)
function to each entry.
Math.rint(double)
function to each entry.
Math.rint(double)
function to each entry.
Math.rint(double)
function to each entry.
Math.signum(double)
function to each entry.
Math.signum(double)
function to each entry.
Math.signum(double)
function to each entry.
Math.sin(double)
function to each entry.
Math.sinh(double)
function to each entry.
Math.sinh(double)
function to each entry.
Math.sinh(double)
function to each entry.
Math.sin(double)
function to each entry.
Math.sin(double)
function to each entry.
Math.sqrt(double)
function to each entry.
Math.sqrt(double)
function to each entry.
Math.sqrt(double)
function to each entry.
Math.tan(double)
function to each entry.
Math.tanh(double)
function to each entry.
Math.tanh(double)
function to each entry.
Math.tanh(double)
function to each entry.
Math.tan(double)
function to each entry.
Math.tan(double)
function to each entry.
Math.ulp(double)
function to each entry.
Math.ulp(double)
function to each entry.
Math.ulp(double)
function to each entry.
MathException
with no
detail message.
MathException.MathException(Localizable, Object...)
MathException
with specified
formatted detail message.
MathException
with specified
nested Throwable
root cause.
MathException.MathException(Throwable, Localizable, Object...)
MathException
with specified
formatted detail message and nested Throwable
root cause.
derivative
.derivative
.integral
method.Math.random()
method.MathRuntimeException.MathRuntimeException(Localizable, Object...)
MathRuntimeException
with specified
formatted detail message.
MathRuntimeException
with specified
nested Throwable
root cause.
MathRuntimeException.MathRuntimeException(Throwable, Localizable, Object...)
MathRuntimeException
with specified
formatted detail message and nested Throwable
root cause.
Math
.matMatModM
using double, but with int instead
of double.
matMatModM
using double, but with long instead
of double.
matPowModM
using double, but with int instead
of double.
matPowModM
using double, but with long instead
of double.
MatrixIndexException.MatrixIndexException(Localizable, Object...)
matTwoPowModM
using double, but with int instead of
double.
matTwoPowModM
using double, but with long instead of
double.
matVecModM
using double, but with int instead
of double.
matVecModM
using double, but with long instead
of double.
Max
identical
to the original
Double.NaN
if the array is empty.
Double.NaN
if the designated subarray
is empty.
MaxEvaluationsExceededException.MaxEvaluationsExceededException(int, Localizable, Object...)
MaxIterationsExceededException.MaxIterationsExceededException(int, Localizable, Object...)
Mean
identical
to the original
Double.NaN
if the array is empty.
Double.NaN
if the designated subarray
is empty.
Median
identical
to the original
Min
identical
to the original
Double.NaN
if the array is empty.
Double.NaN
if the designated subarray
is empty.
RandomStreamBase
, thus
implementing the RandomStream
interface indirectly.RandomStreamBase
by using as a
backbone (or main) generator the combined multiple recursive
generator (CMRG) MRG32k3a proposed by L'Ecuyer,
implemented in 64-bit floating-point arithmetic.MRG32k3a
, except here it is implemented
with type long instead of double.RandomStream
interface via inheritance from
RandomStreamBase
.MullerSolver.solve(UnivariateRealFunction, double, double)
or
UnivariateRealSolver.solve(UnivariateRealFunction, double, double, double)
method.
DiscreteDistributionIntMulti
for the
multinomial distribution with parameters n and
(p1, ...,pd).MultinormalGen
for a multivariate normal distribution, generated via a Cholesky decomposition of the covariance
matrix.MultinormalCholeskyGen
(gen1, mu, new DenseDoubleMatrix2D(sigma)).
ContinuousDistributionMulti
for the
multinormal distribution with mean vector μ and covariance
matrix Σ.RandomMultivariateGen
for a
multivariate normal (or multinormal) distribution.MultinormalGen
for a multivariate normal distribution, generated via the method of principal components analysis
(PCA) of the covariance matrix.MultinormalPCAGen
(gen1, mu, new DenseDoubleMatrix2D(sigma)).
BinaryFunction
.
BigInteger
, returning the result in reduced form.
m
.
m
.
m
.
m
.
m
.
BitVector
by a BitMatrix
and returns the result.
BitVector
, by
a BitMatrix.
DifferentiableMultivariateRealOptimizer
interface adding
multi-start features to an existing optimizer.DifferentiableMultivariateVectorialOptimizer
interface adding
multi-start features to an existing optimizer.MultivariateRealOptimizer
interface adding
multi-start features to an existing optimizer.UnivariateRealOptimizer
interface adding
multi-start features to an existing optimizer.scalar objective functions
.addValue
method.ContinuousDistribution
for
the Nakagami distribution with location parameter a,
scale parameter
λ > 0 and shape parameter c > 0.ClassFinder
when two or more fully qualified class names can be
associated with a simple class name.ComposableFunction
.
DiscreteDistributionInt
for
the negative binomial distribution with real
parameters γ and p, where
γ > 0 and
0 <= p <= 1.DiscreteDistributionIntMulti
for the
negative multinomial distribution with parameters
γ > 0 and
(
p1,…, pd), such that all 0 < pi < 1 and
∑i=1dpi < 1.UnivariateRealSolver
.
UnivariateRealSolver
.
UnivariateRealSolver
.
UnivariateRealSolver
.
UnivariateRealSolver
.
UnivariateRealSolver
.
Dfp
with a value of 0.
Dfp
given a String representation.
Dfp
with a non-finite value.
this
is, with a
given arrayRepresentation
.
UnivariateRealSolver
.
UnivariateRealSolver
.
UnivariateRealSolver
.
UnivariateRealSolver
.
NewtonSolver.solve(UnivariateRealFunction, double, double)
or
UnivariateRealSolver.solve(UnivariateRealFunction, double, double, double)
method.
FastMath.nextAfter(double, double)
which handles Infinities differently, and returns direction if d and direction compare equal.
Beta Distribution
.
Binomial Distribution
.
boolean
value from this random number generator's
sequence.
boolean
value from this random number generator's
sequence.
boolean
value from this random number generator's
sequence.
boolean
value from this random number generator's
sequence.
Cauchy Distribution
.
ChiSquare Distribution
.
(0.0,1.0)
(excluding 0.0 and 1.0).
(0.0,1.0)
(excluding 0.0 and 1.0).
(0.0,1.0)
(excluding 0.0 and 1.0).
(0.0,1.0)
(excluding 0.0 and 1.0).
double
value between 0.0
and
1.0
from this random number generator's sequence.
double
value between 0.0
and
1.0
from this random number generator's sequence.
double
value between 0.0
and
1.0
from this random number generator's sequence.
double
value between 0.0
and
1.0
from this random number generator's sequence.
nextDouble
(s, s, alpha, lambda).
mean
.
F Distribution
.
(0.0f,1.0f)
(excluding 0.0f and 1.0f).
(0.0f,1.0f)
(excluding 0.0f and 1.0f).
(0.0f,1.0f)
(excluding 0.0f and 1.0f).
(0.0f,1.0f)
(excluding 0.0f and 1.0f).
(0.0f,1.0f)
(excluding 0.0f and 1.0f).
float
value between 0.0
and 1.0
from this random
number generator's sequence.
float
value between 0.0
and 1.0
from this random
number generator's sequence.
float
value between 0.0
and 1.0
from this random
number generator's sequence.
float
value between 0.0
and 1.0
from this random
number generator's sequence.
Gamma Distribution
.
double
value with mean 0.0
and standard
deviation 1.0
from this random number generator's sequence.
double
value with mean 0.0
and standard
deviation 1.0
from this random number generator's sequence.
double
value with mean 0.0
and standard
deviation 1.0
from this random number generator's sequence.
double
value with mean 0.0
and standard
deviation 1.0
from this random number generator's sequence.
len
.
len
.
Hypergeometric Distribution
.
int
value from this random number generator's sequence.
int
value
between 0 (inclusive) and the specified value (exclusive), drawn from
this random number generator's sequence.
int
value from this random number generator's sequence.
int
value from this random number generator's sequence.
lower
and upper
(endpoints included).
lower
and upper
, inclusive.
int
value from this random number generator's sequence.
nextDouble
(in which the baker transformation is applied).
long
value from this random number generator's sequence.
long
value from this random number generator's sequence.
long
value from this random number generator's sequence.
lower
and upper
(endpoints included).
lower
and upper
, inclusive.
long
value from this random number generator's sequence.
Pascal Distribution
.
k
whose entries
are selected randomly, without repetition, from the integers
0 through n-1
(inclusive).
k
whose entries are
selected randomly, without repetition, from the integers
0 through n-1
(inclusive).
nextPoint
(gen1, mu, new DenseDoubleMatrix2D(sigma), p).
nextPoint
(gen1, mu, new DenseDoubleMatrix2D(sigma), p).
>= desiredCapacity
and
very close to desiredCapacity
(within 11% if
desiredCapacity >= 1000
).
k
objects selected randomly
from the Collection c
.
lower
and upper
(endpoints included)
from a secure random sequence.
lower
and upper
, inclusive.
lower
and upper
(endpoints included).
lower
and upper
, inclusive.
T Distribution
.
lower
,upper
) (i.e., endpoints excluded).
lower
,upper
) (i.e., endpoints excluded).
Weibull Distribution
.
Zipf Distribution
.
ContinuousDistribution
for the normal
distribution (e.g.,).NormalDist
(for the normal
distribution with mean μ and variance σ2).NormalDistribution
.ContinuousDistribution
for
the normal inverse gaussian distribution with location parameter
μ, scale parameter
δ > 0, tail heavyness
α > 0, and
asymmetry parameter β such that
0 <= | β| < α.InverseGaussianProcess
igP, constructs a
new NormalInverseGaussianProcess.
RandomStream
's
are set to the same stream, streamAll.
NotARotationMatrixException.NotARotationMatrixException(Localizable, Object...)
null
argument must throw
this exception.Object
elements; implemented with arrays.Object
elements; implemented with arrays.ObjectArrayList
to be viewed and treated as a JDK 1.2 AbstractList
.ObjectArrayList
to be
viewed and treated as a JDK 1.2 AbstractList
.fill(int m, int n, 1.0)
instead.
fill(int m, int n, double c)
instead.
fill(int m, double c)
instead.
fill(int m, double c)
instead.
OneWayAnovaImpl
interface.RealVector
interface with a OpenIntToDoubleHashMap
backing store.v
.
v
.
v
.
v
.
v
.
v
.
v
.
v
.
v
.
v
.
v
.
v
.
v
.
v
.
v
.
v
.
OptimizationException.OptimizationException(Localizable, Object...)
sample1
and
sample2
is 0 in favor of the two-sided alternative that the
mean paired difference is not equal to 0, with significance level
alpha
.
sample1
and
sample2
is 0 in favor of the two-sided alternative that the
mean paired difference is not equal to 0, with significance level
alpha
.
ContinuousDistribution
for a distribution
from the Pareto family, with
shape parameter
α > 0 and location parameter β > 0.Complex
object.
Complex
object.
BigFraction
object.
BigFraction
object.
Fraction
object.
Fraction
object.
BigFraction
object.
Fraction
object.
Vector3D
object.
Vector3D
object.
RealVector
object.
RealVector
object.
from
, inclusive, and to
, inclusive.
from
, inclusive, and to
, inclusive.
from
, inclusive, and to
, inclusive.
from
, inclusive, and to
, inclusive.
from
, inclusive, and to
, inclusive.
from
, inclusive, and to
, inclusive.
from
, inclusive, and to
, inclusive.
from
, inclusive, and to
, inclusive.
from
, inclusive, and to
, inclusive.
from
, inclusive, and to
, inclusive.
from
, inclusive, and to
, inclusive.
from
, inclusive, and to
, inclusive.
from
, inclusive, and to
, inclusive.
from
, inclusive, and to
, inclusive.
from
, inclusive, and to
, inclusive.
from
, inclusive, and to
, inclusive.
from
, inclusive, and to
, inclusive.
from
,
inclusive, and to
, inclusive.
from
,
inclusive, and to
, inclusive.
from
,
inclusive, and to
, inclusive.
from
,
inclusive, and to
, inclusive.
from
,
inclusive, and to
, inclusive.
from
,
inclusive, and to
, inclusive.
from
,
inclusive, and to
, inclusive.
from
,
inclusive, and to
, inclusive.
from
,
inclusive, and to
, inclusive.
from
,
inclusive, and to
, inclusive.
from
,
inclusive, and to
, inclusive.
from
,
inclusive, and to
, inclusive.
from
,
inclusive, and to
, inclusive.
from
,
inclusive, and to
, inclusive.
from
,
inclusive, and to
, inclusive.
from
,
inclusive, and to
, inclusive.
from
,
inclusive, and to
, inclusive.
Partitioning.partition(int[],int,int,int[],int,int,int[])
except that it synchronously partitions the rows of the given matrix by the values of the given matrix column;
This is essentially the same as partitioning a list of composite objects by some instance variable;
In other words, two entire rows of the matrix are swapped, whenever two column values indicate so.
Partitioning.partition(int[],int,int,int[],int,int,int[])
except that it synchronously partitions the rows of the given matrix by the values of the given matrix column;
This is essentially the same as partitioning a list of composite objects by some instance variable;
In other words, two entire rows of the matrix are swapped, whenever two column values indicate so.
Partitioning.partition(int[],int,int,int[],int,int,int[])
except that it synchronously partitions the rows of the given matrix by the values of the given matrix column;
This is essentially the same as partitioning a list of composite objects by some instance variable;
In other words, two entire rows of the matrix are swapped, whenever two column values indicate so.
Partitioning.partition(int[],int,int,int[],int,int,int[])
except that it synchronously partitions the rows of the given matrix by the values of the given matrix column;
This is essentially the same as partitioning a list of composite objects by some instance variable;
In other words, two entire rows of the matrix are swapped, whenever two column values indicate so.
Partitioning.partition(int[],int,int,int[],int,int,int[])
except that it synchronously partitions the rows of the given
matrix by the values of the given matrix column; This is essentially the
same as partitioning a list of composite objects by some instance
variable; In other words, two entire rows of the matrix are swapped,
whenever two column values indicate so.
Partitioning.partition(int[],int,int,int[],int,int,int[])
except that it synchronously partitions the rows of the given
matrix by the values of the given matrix column; This is essentially the
same as partitioning a list of composite objects by some instance
variable; In other words, two entire rows of the matrix are swapped,
whenever two column values indicate so.
Partitioning.partition(int[],int,int,int[],int,int,int[])
except that it synchronously partitions the rows of the given
matrix by the values of the given matrix column; This is essentially the
same as partitioning a list of composite objects by some instance
variable; In other words, two entire rows of the matrix are swapped,
whenever two column values indicate so.
Partitioning.partition(int[],int,int,int[],int,int,int[])
except that it synchronously partitions the rows of the given
matrix by the values of the given matrix column; This is essentially the
same as partitioning a list of composite objects by some instance
variable; In other words, two entire rows of the matrix are swapped,
whenever two column values indicate so.
Partitioning.partition(int[],int,int,int[],int,int,int[])
except that it synchronously partitions the rows of the given
matrix by the values of the given matrix column; This is essentially the
same as partitioning a list of composite objects by some instance
variable; In other words, two entire rows of the matrix are swapped,
whenever two column values indicate so.
Partitioning.partition(int[],int,int,int[],int,int,int[])
except that it synchronously partitions the rows of the given
matrix by the values of the given matrix column; This is essentially the
same as partitioning a list of composite objects by some instance
variable; In other words, two entire rows of the matrix are swapped,
whenever two column values indicate so.
Partitioning.partition(int[],int,int,int[],int,int,int[])
except that
it partitions double[] rather than int[] arrays.
Partitioning.partition(int[],int,int,int)
except that it partitions
double[] rather than int[] arrays.
Partitioning.partition(int[],int,int,int[],int,int,int[])
except that
it partitions Object[] rather than int[] arrays.
Partitioning.partition(int[],int,int,int)
except that it
synchronously partitions the objects of the given list by the
order of the given comparator.
PascalDistribution
.InverseGammaDist
.InverseGammaDist
.
InverseGammaGen
.InverseGammaGen
.
ContinuousDistribution
for
the Pearson type VI distribution with shape parameters
α1 > 0 and
α2 > 0, and scale parameter β > 0.Covariance
.
Percentile
identical
to the original
p
th percentile of the values
in the values
array.
p
th percentile of the values
in the values
array, starting with the element in (0-based)
position begin
in the array and including length
values.
DoubleMatrix2D.viewSelection(int[],int[])
.
DoubleMatrix2D.viewSelection(int[],int[])
.
FloatMatrix2D.viewSelection(int[],int[])
.
ContinuousDistribution
for a piecewise-linear
approximation of the empirical distribution function,
based on the observations
X(1),..., X(n) (sorted by increasing order),
and defined as follows (e.g.,).PointSet
.DiscreteDistributionInt
for the
Poisson distribution with mean
λ >= 0.PoissonDistribution
.PoissonGen
).FastMath.pow
method wrapped as a BinaryFunction
.
x
.
BigFraction
whose value is
(thisexponent), returning the result in reduced form.
BigFraction
whose value is
(thisexponent), returning the result in reduced form.
double
whose value is
(thisexponent), returning the result in reduced form.
other constructor
).
other constructor
).
ContinuousDistribution
for
the power distribution with shape parameter
c > 0, over the interval [a, b], where a < b.y
value associated with the
supplied x
value, based on the data that has been
added to the model when this method is activated.
m
.
v
.
v
.
m
.
v
.
v
.
v
.
v
.
m
.
v
.
m
.
v
.
v
.
v
.
m
.
v
.
v
.
m
.
v
.
v
.
v
.
String
containing all the data of
the BitMatrix.
StringBuffer
which defines new types
of append methods.Product
identical
to the original
Double.NaN
if the array is empty.
Double.NaN
if the designated subarray
is empty.
from
to index to
to the bits of value
.
from
to index to
to the bits of value
.
from
to index
to
to the bits of value
.
from
to index
to
to the bits of value
.
(0.0,1.0)
(excluding 0.0 and 1.0).
(0.0,1.0)
(excluding 0.0 and 1.0).
(0.0,1.0)
(excluding 0.0 and 1.0).
java.util.Random
wrapping a
RandomGenerator
.length
.
RandomData
interface using a RandomGenerator
instance to generate non-secure data and a SecureRandom
instance to provide data for the nextSecureXxx
methods.RandomGenerator
as
the source of (non-secure) random data.
java.util.Random
.leftMatrixScramble
,
then
addRandomShift
.
addRandomShift
(stream).
stripedMatrixScramble
,
then
addRandomShift
.
RandomKey
s.RandomVariateGen
.Random
object.Random
delegate.
Random
delegate initialized with the given seed.
Random
delegate.
PointSetRandomization
.RandomStream
to stream.
newInstance
method
each time a new random stream is needed, instead of invoking
directly the specific constructor of the desired type.newInstance
method.data
using the natural ordering on Doubles, with
NaN values handled according to nanStrategy
and ties
resolved using tiesStrategy.
Rank1Lattice
with n points and lattice
vector a of dimension s.
(0.0,1.0)
(excluding 0.0 and 1.0).
(0.0,1.0)
(excluding 0.0 and 1.0).
(0.0,1.0)
(excluding 0.0 and 1.0).
(0.0,1.0)
(excluding 0.0 and 1.0).
(0.0,1.0)
(excluding 0.0 and 1.0).
(0.0,1.0)
(excluding 0.0 and 1.0).
(0.0,1.0)
(excluding 0.0 and 1.0).
ContinuousDistribution
for
the Rayleigh distribution with
location parameter a, and scale parameter β > 0.readCSVData
to
obtain a matrix of strings from
the resource.
readDoubleData2D
,
for reading strings.
readDoubleData2D
,
for reading strings.
readDoubleData
to
obtain an array of double-precision values from
the resource.
readDoubleData
to
obtain an array of double-precision values from
the file.
readDoubleData
to
obtain an array of double-precision values from
the file.
readDoubleData2D
to
obtain a matrix of double-precision values from
the resource.
readDoubleData2D
to
obtain a matrix of double-precision values from
the file.
readDoubleData2D
to
obtain a matrix of double-precision values from
the file.
readDoubleData
,
for reading integers.
readIntData
to
obtain an array of integers from
the resource.
readDoubleData
,
for reading integers.
readDoubleData
,
for reading integers.
readDoubleData2D
,
for reading integers.
readDoubleData
to
obtain a matrix of integers from
the resource.
readDoubleData2D
,
for reading integers.
readDoubleData2D
,
for reading integers.
readStringData
to
obtain an array of integers from
the resource.
readDoubleData
,
for reading strings.
readDoubleData
,
for reading strings.
optimization
algorithm
has converged.Array2DRowRealMatrix
v
as the
data for the unique column of the v.length x 1
matrix
created.
EventList
using a red black tree,
which is similar to a binary search tree except that
every node is colored red or black.BigFraction
to its lowest terms.
LinearConstraint
.data
.
from
, inclusive and to
, inclusive.
from
, inclusive and to
, inclusive.
from
, inclusive and to
, inclusive.
from
, inclusive and to
, inclusive.
from
, inclusive and to
, inclusive.
from
, inclusive and to
, inclusive.
from
, inclusive and to
, inclusive.
from
, inclusive and to
, inclusive.
from
, inclusive and to
, inclusive.
from
, inclusive and to
, inclusive.
from
, inclusive and to
, inclusive.
from
, inclusive and to
, inclusive.
from
, inclusive and to
, inclusive.
from
, inclusive and to
, inclusive.
from
, inclusive and to
, inclusive.
from
, inclusive and to
, inclusive.
from
, inclusive and to
, inclusive.
from
, inclusive and to
, inclusive.
from
, inclusive and to
, inclusive.
from
, inclusive and to
, inclusive.
from
, inclusive and to
, inclusive.
from
(inclusive) and to
(inclusive) with the other list's
part between otherFrom
and otherTo
.
from
(inclusive) and to
(inclusive) with the other list's
part between otherFrom
and otherTo
.
from
(inclusive) and to
(inclusive) with the other list's
part between otherFrom
and otherTo
.
from
(inclusive) and to
(inclusive) with the other list's
part between otherFrom
and otherTo
.
from
(inclusive) and to
(inclusive) with the other list's
part between otherFrom
and otherTo
.
from
(inclusive) and to
(inclusive) with the other list's
part between otherFrom
and otherTo
.
from
(inclusive) and to
(inclusive) with the other list's
part between otherFrom
and otherTo
.
from
(inclusive) and to
(inclusive) with the other list's
part between otherFrom
and otherTo
.
from
(inclusive) and to
(inclusive) with the other list's
part between otherFrom
and otherTo
.
from
(inclusive) and
to
(inclusive) with the other list's part between
otherFrom
and otherTo
.
from
(inclusive) and
to
(inclusive) with the other list's part between
otherFrom
and otherTo
.
from
(inclusive) and
to
(inclusive) with the other list's part between
otherFrom
and otherTo
.
from
(inclusive) and
to
(inclusive) with the other list's part between
otherFrom
and otherTo
.
from
(inclusive) and
to
(inclusive) with the other list's part between
otherFrom
and otherTo
.
from
(inclusive) and
to
(inclusive) with the other list's part between
otherFrom
and otherTo
.
from
(inclusive) and
to
(inclusive) with the other list's part between
otherFrom
and otherTo
.
from
(inclusive) and
to
(inclusive) with the other list's part between
otherFrom
and otherTo
.
from
(inclusive) and
to
(inclusive) with the other list's part between
otherFrom
and otherTo
.
from
(inclusive) with all the elements of the specified collection.
from
(inclusive) with all the elements of the specified collection.
from
(inclusive) with all the elements of the specified collection.
from
(inclusive) with all the elements of the specified collection.
from
(inclusive) with all the elements of the specified collection.
from
(inclusive) with all the elements of the specified collection.
from
(inclusive) with all the elements of the specified collection.
from
(inclusive) with all the elements of the specified collection.
from
(inclusive) with all the elements of the specified collection.
from
(inclusive) with all the elements of the specified collection.
from
(inclusive) with all the elements of the specified collection.
from
(inclusive) with all the elements of the specified collection.
from
(inclusive) with all the elements of the specified collection.
from
(inclusive) with all the elements of the specified collection.
from
(inclusive) with all the elements of the specified collection.
from
(inclusive) with all the elements of the specified collection.
from
(inclusive) with all the elements of the specified collection.
from
(inclusive) with all the elements of the specified collection.
from
(inclusive) with all the elements of the specified collection.
setStatCollecting
(true) has been
called before for this list.
report
, except that
probes is an Iterable
object instead of an array.
report
), followed by a confidence interval (as in
formatCIStudent
), using d fractional decimal digits.
reportAndCIStudent
(level, 3).
setCurCoordIndex
(0).
setCurPointIndex
(0).
resetNextSubstream
methods
of all streams in the list.
valuesFileURL
.
VarianceGammaProcess
object used to generate this process.
BrownianMotion
and the GammaProcess
objects
used to generate this process.
GammaProcess
objects used to generate this process.
resetStartStream
methods
of all streams in the list.
resetStartSubstream
methods
of all streams in the list.
DoubleArray
implementation that automatically
handles expanding and contracting its internal storage array as elements
are added and removed.Process
objects.{n-1, ....
- reverse() -
Method in class jhplot.P0D
- Reverse the order of elements
- reverse() -
Method in class jhplot.P0I
- Reverse the order of elements
- reverseArray(double[]) -
Static method in class flanagan.math.Fmath
-
- reverseArray(float[]) -
Static method in class flanagan.math.Fmath
-
- reverseArray(int[]) -
Static method in class flanagan.math.Fmath
-
- reverseArray(long[]) -
Static method in class flanagan.math.Fmath
-
- reverseArray(char[]) -
Static method in class flanagan.math.Fmath
-
- reverseDigits(int, int[], int[]) -
Static method in class umontreal.iro.lecuyer.hups.RadicalInverse
- Given the k b-ary digits of i in bdigits, returns the
k digits of the integer radical inverse of i in idigits.
- reverseYsign(String) -
Method in class flanagan.analysis.Regression
-
- revert() -
Method in class org.apache.commons.math.geometry.Rotation
- Revert a rotation.
- richardson(int, F1D, double, double) -
Static method in class jhplot.math.Numeric
- Numerical integration using the Richardson extrapolation.
- RiddersSolver - Class in org.apache.commons.math.analysis.solvers
- Implements the
Ridders' Method for root finding of real univariate functions.
- RiddersSolver(UnivariateRealFunction) -
Constructor for class org.apache.commons.math.analysis.solvers.RiddersSolver
- Deprecated. as of 2.0 the function to solve is passed as an argument
to the
RiddersSolver.solve(UnivariateRealFunction, double, double)
or
UnivariateRealSolver.solve(UnivariateRealFunction, double, double, double)
method.
- RiddersSolver() -
Constructor for class org.apache.commons.math.analysis.solvers.RiddersSolver
- Deprecated. in 2.2
- RIGHT -
Static variable in class cern.colt.matrix.AbstractFormatter
- The alignment string aligning the cells of a column to the right.
- RIGHT -
Static variable in class cern.colt.matrix.impl.AbstractFormatter
- The alignment string aligning the cells of a column to the right.
- rightMatrixScramble(RandomStream) -
Method in class umontreal.iro.lecuyer.hups.DigitalNet
- Applies a linear scramble by multiplying each
Cj on the right
by a single k×k nonsingular upper-triangular matrix
M,
as suggested by Faure and Tezuka.
- rightMatrixScramble(RandomStream) -
Method in class umontreal.iro.lecuyer.hups.DigitalNetBase2
-
- rightWithin(Rectangle, Dimension) -
Static method in class jhplot.v3d.Util
-
- rightWithin(Component, Component) -
Static method in class jhplot.v3d.Util
- Puts to the right
- rint -
Static variable in class cern.jet.math.Functions
- Function that returns Math.rint(a).
- rint -
Static variable in class cern.jet.math.tdouble.DoubleFunctions
- Function that returns Math.rint(a).
- rint -
Static variable in class cern.jet.math.tfloat.FloatFunctions
- Function that returns Math.rint(a).
- rint() -
Method in class flanagan.analysis.Stat
-
- rint() -
Method in class flanagan.math.ArrayMaths
-
- RINT -
Static variable in class org.apache.commons.math.analysis.ComposableFunction
- The
FastMath.rint
method wrapped as a ComposableFunction
.
- rint() -
Method in class org.apache.commons.math.dfp.Dfp
- Round to nearest integer using the round-half-even method.
- rint(double) -
Static method in class org.apache.commons.math.util.FastMath
- Get the whole number that is the nearest to x, or the even one if x is exactly half way between two integers.
- rm(String) -
Method in class hep.aida.ref.tree.Tree
- Remove an IManagedObject by specifying its path.
- rmdir(String) -
Method in class hep.aida.ref.tree.Tree
- Remove a directory and all the contents underneath.
- rms() -
Method in class cern.hep.aida.bin.AbstractBin1D
- Returns the rms (Root Mean Square), which is Math.sqrt( Sum( x[i]*x[i] ) / size() ).
- rms -
Static variable in class cern.hep.aida.bin.BinFunctions1D
- Function that returns bin.rms().
- rms() -
Method in class cern.hep.aida.ref.Histogram1D
-
- rms(int, double) -
Static method in class cern.jet.stat.Descriptive
- Returns the RMS (Root-Mean-Square) of a data sequence.
- rms(int, double) -
Static method in class cern.jet.stat.tdouble.DoubleDescriptive
- Returns the RMS (Root-Mean-Square) of a data sequence.
- rms(int, float) -
Static method in class cern.jet.stat.tfloat.FloatDescriptive
- Returns the RMS (Root-Mean-Square) of a data sequence.
- rms() -
Method in class flanagan.analysis.Stat
-
- rms(double[]) -
Static method in class flanagan.analysis.Stat
-
- rms(float[]) -
Static method in class flanagan.analysis.Stat
-
- rms(BigDecimal[]) -
Static method in class flanagan.analysis.Stat
-
- rms(BigInteger[]) -
Static method in class flanagan.analysis.Stat
-
- rms(double[], double[]) -
Static method in class flanagan.analysis.Stat
-
- rms(float[], float[]) -
Static method in class flanagan.analysis.Stat
-
- rms(BigDecimal[], BigDecimal[]) -
Static method in class flanagan.analysis.Stat
-
- rms(BigInteger[], BigInteger[]) -
Static method in class flanagan.analysis.Stat
-
- rms(int[], int) -
Method in interface hep.aida.ref.dataset.binner.Binner
- Get the rms of a bin along a given coordinate.
- rms(int[], int) -
Method in class hep.aida.ref.dataset.binner.DefaultBinner
- Get the rms of a bin along a given coordinate.
- rms(int) -
Method in class hep.aida.ref.dataset.DataStatistics
- Get the rms for a given coordinate.
- rms(int) -
Method in class hep.aida.ref.histogram.binner.AbstractBinner1D
-
- rms(int) -
Method in interface hep.aida.ref.histogram.binner.Binner1D
-
- rms() -
Method in class hep.aida.ref.histogram.Cloud1D
- Get the Cloud's rms.
- rms() -
Method in class hep.aida.ref.histogram.Histogram1D
- Get the RMS of the whole Histogram.
- rms() -
Method in class hep.aida.ref.histogram.Profile1D
-
- rms() -
Method in class hep.aida.ref.tuple.AbstractTuple.AbstractTupleColumnFactory.BaseTupleColumn
-
- rms() -
Method in class hep.aida.ref.tuple.TupleColumn
-
- rms() -
Method in class hep.aida.tdouble.bin.AbstractDoubleBin1D
- Returns the rms (Root Mean Square), which is
Math.sqrt( Sum( x[i]*x[i] ) / size() ).
- rms -
Static variable in class hep.aida.tdouble.bin.DoubleBinFunctions1D
- Function that returns bin.rms().
- rms() -
Method in interface hep.aida.tdouble.DoubleIHistogram1D
- Returns the rms of the whole histogram as calculated on filling-time.
- rms() -
Method in class hep.aida.tdouble.ref.DoubleHistogram1D
-
- rms() -
Method in class hep.aida.tfloat.bin.AbstractFloatBin1D
- Returns the rms (Root Mean Square), which is
Math.sqrt( Sum( x[i]*x[i] ) / size() ).
- rms -
Static variable in class hep.aida.tfloat.bin.FloatBinFunctions1D
- Function that returns bin.rms().
- rms() -
Method in interface hep.aida.tfloat.FloatIHistogram1D
- Returns the rms of the whole histogram as calculated on filling-time.
- rms() -
Method in class hep.aida.tfloat.ref.FloatHistogram1D
-
- rms() -
Method in class jhplot.H1D
- Get RMS of histogram
- rms() -
Method in class jhplot.HProf1D
- Get RMS of histogram
- rmsValue(Value) -
Method in class hep.aida.ref.tuple.AbstractTuple.AbstractTupleColumnFactory.BaseTupleColumn
-
- rmsValue(Value) -
Method in interface hep.aida.ref.tuple.FTupleColumn
-
- rmsValue(Value) -
Method in class hep.aida.ref.tuple.TupleColumn
-
- rmsX() -
Method in class cern.hep.aida.ref.Histogram2D
-
- rmsX() -
Method in class cern.hep.aida.ref.Histogram3D
-
- rmsX(int, int) -
Method in class hep.aida.ref.histogram.binner.BasicBinner2D
-
- rmsX(int, int, int) -
Method in class hep.aida.ref.histogram.binner.BasicBinner3D
-
- rmsX(int, int) -
Method in interface hep.aida.ref.histogram.binner.Binner2D
-
- rmsX(int, int, int) -
Method in interface hep.aida.ref.histogram.binner.Binner3D
-
- rmsX(int, int) -
Method in class hep.aida.ref.histogram.binner.EfficiencyBinner2D
-
- rmsX(int, int, int) -
Method in class hep.aida.ref.histogram.binner.EfficiencyBinner3D
-
- rmsX() -
Method in class hep.aida.ref.histogram.Cloud2D
- Get the Cloud's x rms.
- rmsX() -
Method in class hep.aida.ref.histogram.Cloud3D
- Get the Cloud's x rms.
- rmsX() -
Method in class hep.aida.ref.histogram.Histogram2D
- Get the RMS of the whole Histogram as projected on the x axis.
- rmsX() -
Method in class hep.aida.ref.histogram.Histogram3D
- Get the RMS of the whole Histogram as projected on the x axis.
- rmsX() -
Method in class hep.aida.ref.histogram.Profile2D
-
- rmsX() -
Method in interface hep.aida.tdouble.DoubleIHistogram2D
- Returns the rms of the histogram as calculated on filling-time projected
on the X axis.
- rmsX() -
Method in interface hep.aida.tdouble.DoubleIHistogram3D
- Returns the rms of the histogram as calculated on filling-time projected
on the X axis.
- rmsX() -
Method in class hep.aida.tdouble.ref.DoubleHistogram2D
-
- rmsX() -
Method in class hep.aida.tdouble.ref.DoubleHistogram3D
-
- rmsX() -
Method in interface hep.aida.tfloat.FloatIHistogram2D
- Returns the rms of the histogram as calculated on filling-time projected
on the X axis.
- rmsX() -
Method in interface hep.aida.tfloat.FloatIHistogram3D
- Returns the rms of the histogram as calculated on filling-time projected
on the X axis.
- rmsX() -
Method in class hep.aida.tfloat.ref.FloatHistogram2D
-
- rmsX() -
Method in class hep.aida.tfloat.ref.FloatHistogram3D
-
- rmsX() -
Method in class jhplot.P1D
- Returns RMS for X-values.
- rmsY() -
Method in class cern.hep.aida.ref.Histogram2D
-
- rmsY() -
Method in class cern.hep.aida.ref.Histogram3D
-
- rmsY(int, int) -
Method in class hep.aida.ref.histogram.binner.BasicBinner2D
-
- rmsY(int, int, int) -
Method in class hep.aida.ref.histogram.binner.BasicBinner3D
-
- rmsY(int, int) -
Method in interface hep.aida.ref.histogram.binner.Binner2D
-
- rmsY(int, int, int) -
Method in interface hep.aida.ref.histogram.binner.Binner3D
-
- rmsY(int, int) -
Method in class hep.aida.ref.histogram.binner.EfficiencyBinner2D
-
- rmsY(int, int, int) -
Method in class hep.aida.ref.histogram.binner.EfficiencyBinner3D
-
- rmsY() -
Method in class hep.aida.ref.histogram.Cloud2D
- Get the Cloud's y rms.
- rmsY() -
Method in class hep.aida.ref.histogram.Cloud3D
- Get the Cloud's y rms.
- rmsY() -
Method in class hep.aida.ref.histogram.Histogram2D
- Get the RMS of the whole Histogram as projected on the y axis.
- rmsY() -
Method in class hep.aida.ref.histogram.Histogram3D
- Get the RMS of the whole Histogram as projected on the y axis.
- rmsY() -
Method in class hep.aida.ref.histogram.Profile2D
-
- rmsY() -
Method in interface hep.aida.tdouble.DoubleIHistogram2D
- Returns the rms of the histogram as calculated on filling-time projected
on the Y axis.
- rmsY() -
Method in interface hep.aida.tdouble.DoubleIHistogram3D
- Returns the rms of the histogram as calculated on filling-time projected
on the Y axis.
- rmsY() -
Method in class hep.aida.tdouble.ref.DoubleHistogram2D
-
- rmsY() -
Method in class hep.aida.tdouble.ref.DoubleHistogram3D
-
- rmsY() -
Method in interface hep.aida.tfloat.FloatIHistogram2D
- Returns the rms of the histogram as calculated on filling-time projected
on the Y axis.
- rmsY() -
Method in interface hep.aida.tfloat.FloatIHistogram3D
- Returns the rms of the histogram as calculated on filling-time projected
on the Y axis.
- rmsY() -
Method in class hep.aida.tfloat.ref.FloatHistogram2D
-
- rmsY() -
Method in class hep.aida.tfloat.ref.FloatHistogram3D
-
- rmsY() -
Method in class jhplot.P1D
- Returns RMS for Y-values.
- rmsZ() -
Method in class cern.hep.aida.ref.Histogram3D
-
- rmsZ(int, int, int) -
Method in class hep.aida.ref.histogram.binner.BasicBinner3D
-
- rmsZ(int, int, int) -
Method in interface hep.aida.ref.histogram.binner.Binner3D
-
- rmsZ(int, int, int) -
Method in class hep.aida.ref.histogram.binner.EfficiencyBinner3D
-
- rmsZ() -
Method in class hep.aida.ref.histogram.Cloud3D
- Get the Cloud's z rms.
- rmsZ() -
Method in class hep.aida.ref.histogram.Histogram3D
- Get the RMS of the whole Histogram as projected on the z axis.
- rmsZ() -
Method in interface hep.aida.tdouble.DoubleIHistogram3D
- Returns the rms of the histogram as calculated on filling-time projected
on the Z axis.
- rmsZ() -
Method in class hep.aida.tdouble.ref.DoubleHistogram3D
-
- rmsZ() -
Method in interface hep.aida.tfloat.FloatIHistogram3D
- Returns the rms of the histogram as calculated on filling-time projected
on the Z axis.
- rmsZ() -
Method in class hep.aida.tfloat.ref.FloatHistogram3D
-
- RNG - Interface in jhplot.math.num.random
- Defines a random number generator that is capable of generating sequences of
random numbers uniformly distributed between zero and one.
- RombergIntegrator - Class in jhplot.math.num.integration
-
An implementation of Romberg Integration.
- RombergIntegrator(Function) -
Constructor for class jhplot.math.num.integration.RombergIntegrator
- Create an integrator for the given function.
- RombergIntegrator(Function, int, double) -
Constructor for class jhplot.math.num.integration.RombergIntegrator
- Create an integrator for the given function.
- RombergIntegrator - Class in org.apache.commons.math.analysis.integration
- Implements the
Romberg Algorithm for integration of real univariate functions.
- RombergIntegrator(UnivariateRealFunction) -
Constructor for class org.apache.commons.math.analysis.integration.RombergIntegrator
- Deprecated. as of 2.0 the integrand function is passed as an argument
to the
RombergIntegrator.integrate(UnivariateRealFunction, double, double)
method.
- RombergIntegrator() -
Constructor for class org.apache.commons.math.analysis.integration.RombergIntegrator
- Construct an integrator.
- RootFinder - Class in umontreal.iro.lecuyer.util
- This class provides methods to solve non-linear equations.
- RootHistogramBrowser - Class in jhplot.root
- A simple application for browsing histograms in Root Files
- RootHistogramBrowser() -
Constructor for class jhplot.root.RootHistogramBrowser
- Histogram browser
- rotatedCumulativePercentage() -
Method in class flanagan.analysis.PCA
-
- rotatedEigenValues() -
Method in class flanagan.analysis.PCA
-
- rotatedLoadingFactorsAsColumns() -
Method in class flanagan.analysis.PCA
-
- rotatedLoadingFactorsAsRows() -
Method in class flanagan.analysis.PCA
-
- rotatedProportionPercentage() -
Method in class flanagan.analysis.PCA
-
- Rotation - Class in org.apache.commons.math.geometry
- This class implements rotations in a three-dimensional space.
- Rotation(double, double, double, double, boolean) -
Constructor for class org.apache.commons.math.geometry.Rotation
- Build a rotation from the quaternion coordinates.
- Rotation(Vector3D, double) -
Constructor for class org.apache.commons.math.geometry.Rotation
- Build a rotation from an axis and an angle.
- Rotation(double[][], double) -
Constructor for class org.apache.commons.math.geometry.Rotation
- Build a rotation from a 3X3 matrix.
- Rotation(Vector3D, Vector3D, Vector3D, Vector3D) -
Constructor for class org.apache.commons.math.geometry.Rotation
- Build the rotation that transforms a pair of vector into another pair.
- Rotation(Vector3D, Vector3D) -
Constructor for class org.apache.commons.math.geometry.Rotation
- Build one of the rotations that transform one vector into another one.
- Rotation(RotationOrder, double, double, double) -
Constructor for class org.apache.commons.math.geometry.Rotation
- Build a rotation from three Cardan or Euler elementary rotations.
- RotationOrder - Class in org.apache.commons.math.geometry
- This class is a utility representing a rotation order specification
for Cardan or Euler angles specification.
- round(double) -
Static method in class cern.jet.math.Functions
- Constructs a function that returns the number rounded to the given precision; Math.rint(a/precision)*precision.
- round(double) -
Static method in class cern.jet.math.tdouble.DoubleFunctions
- Constructs a function that returns the number rounded to the given
precision; Math.rint(a/precision)*precision.
- round(float) -
Static method in class cern.jet.math.tfloat.FloatFunctions
- Constructs a function that returns the number rounded to the given
precision; Math.rint(a/precision)*precision.
- round(double) -
Static method in class org.apache.commons.math.util.FastMath
- Get the closest long to x.
- round(float) -
Static method in class org.apache.commons.math.util.FastMath
- Get the closest int to x.
- round(double, int) -
Static method in class org.apache.commons.math.util.MathUtils
- Round the given value to the specified number of decimal places.
- round(double, int, int) -
Static method in class org.apache.commons.math.util.MathUtils
- Round the given value to the specified number of decimal places.
- round(float, int) -
Static method in class org.apache.commons.math.util.MathUtils
- Round the given value to the specified number of decimal places.
- round(float, int, int) -
Static method in class org.apache.commons.math.util.MathUtils
- Round the given value to the specified number of decimal places.
- roundDown(double, int) -
Static method in class hep.aida.ref.AidaUtils
- Round number down (closer to Negative Infinity):
"order" defines which significant digit is rounded, order >= 0
roundDown(234.5, 0) -> 200.0
roundDown(234.5, 1) -> 230.0
roundDown(234.5, 2) -> 234.0
- roundUp(double, int) -
Static method in class hep.aida.ref.AidaUtils
- Round number up (closer to Positive Infinity),
"order" defines which significant digit is rounded, order >= 0
roundUp(234.5, 0) -> 300.0
roundUp(234.5, 1) -> 240.0
roundUp(234.5, 2) -> 235.0
- row() -
Method in interface hep.aida.ref.tuple.FTupleCursor
-
- row() -
Method in class hep.aida.ref.tuple.TupleCursor
-
- rowCompressed -
Static variable in class cern.colt.matrix.DoubleFactory2D
- A factory producing sparse row compressed matrices.
- rowCompressed -
Static variable in class cern.colt.matrix.tint.IntFactory2D
- A factory producing sparse row compressed matrices.
- rowCompressed -
Static variable in class cern.colt.matrix.tlong.LongFactory2D
- A factory producing sparse row compressed matrices.
- rowMatrix(double[]) -
Static method in class flanagan.math.Matrix
-
- rowMaxima() -
Method in class flanagan.math.Matrix
-
- rowMeans() -
Method in class flanagan.math.Matrix
-
- rowMedians() -
Method in class flanagan.math.Matrix
-
- rowMinima() -
Method in class flanagan.math.Matrix
-
- rowRanges() -
Method in class flanagan.math.Matrix
-
- rows() -
Method in class cern.colt.bitvector.BitMatrix
- Returns the number of rows of the receiver.
- rows() -
Method in class cern.colt.matrix.AbstractMatrix2D
- Returns the number of rows.
- rows() -
Method in class cern.colt.matrix.AbstractMatrix3D
- Returns the number of rows.
- rows() -
Method in class cern.colt.matrix.impl.AbstractMatrix2D
- Returns the number of rows.
- rows() -
Method in class cern.colt.matrix.impl.AbstractMatrix3D
- Returns the number of rows.
- rows() -
Method in class cern.colt.matrix.tbit.BitMatrix
- Returns the number of rows of the receiver.
- rows() -
Method in class hep.aida.ref.tuple.AbstractTuple
-
- rows() -
Method in class hep.aida.ref.tuple.ChainedTuple
- The number of rows currently in the ntuple.
- rows() -
Method in interface hep.aida.ref.tuple.FTuple
-
- rows() -
Method in class hep.aida.ref.tuple.FTupleAdapter
-
- rows() -
Method in class hep.aida.ref.tuple.Tuple
-
- ROWS_UNKNOWN -
Static variable in interface hep.aida.ref.tuple.FTuple
-
- rowStandardDeviations() -
Method in class flanagan.math.Matrix
-
- rowStandardErrors() -
Method in class flanagan.math.Matrix
-
- rowStride() -
Method in class cern.colt.matrix.AbstractMatrix2D
- Returns the row stride.
- rowStride() -
Method in class cern.colt.matrix.AbstractMatrix3D
- Returns the row stride.
- rowSums() -
Method in class flanagan.math.Matrix
-
- rowVariances() -
Method in class flanagan.math.Matrix
-
- rowVector(double[]) -
Static method in class jhplot.math.DoubleArray
- Converts an n element array into an 1 x n matrix.
- rr -
Variable in class jhplot.io.HDataBase
-
- run() -
Method in class jhplot.HBsom
- Run the algorithm
- run(double[]) -
Method in class jhplot.stat.BunchingParameters
- Collect information about sampling.
- run(double[]) -
Method in class jhplot.stat.FactorialMoments
- Collect information about sampling.
- run() -
Method in class jhplot.v3d.Animation
-
- run(boolean) -
Method in class jhpro.stat.limit.StatConfidence
- Run limit calculations.
- run(int) -
Method in class jminhep.cluster.Partition
- Main method to run cluster algorithm
- RungeKutta - Class in flanagan.integration
-
- RungeKutta() -
Constructor for class flanagan.integration.RungeKutta
-
- rungeKutta2(double[], F1D, double) -
Static method in class jhplot.math.Numeric
- Uses the 2nd order Runge-Kutta method to solve an ODE.
- rungeKutta4(double[], F1D, double) -
Static method in class jhplot.math.Numeric
- Uses the 4th order Runge-Kutta method to solve an ODE.
- RungeKuttaIntegrator - Class in org.apache.commons.math.ode.nonstiff
- This class implements the common part of all fixed step Runge-Kutta
integrators for Ordinary Differential Equations.
- rw -
Variable in class jhplot.io.HDataBase
-
- rxy() -
Method in class hephysics.vec.SpacePoint
- Cylindrical r
- rxyz() -
Method in class hephysics.vec.SpacePoint
- Spherical r
s
(0, str).
d
FastMath.scalb(double, int)
FBar.scan
.
SecantSolver.solve(UnivariateRealFunction, double, double)
or
UnivariateRealSolver.solve(UnivariateRealFunction, double, double, double)
method.
SecondMoment
identical
to the original
biasCorrected
property and default (Downside) varianceDirection
property.
biasCorrected
property and default (Downside) varianceDirection
property.
Direction
property
and default (true) biasCorrected
property
isBiasCorrected
property and the specified Direction
property.
SemiVariance
identical
to the original
RealMatrix
.
RealVector
.
UserRecord
objects
for the processes in the service list for this resource.
nextDouble
.
nextDouble
.
column
as a column matrix.
column
as a column matrix.
column
as a column matrix.
column
as a column matrix.
column
as a column matrix.
column
as a column matrix.
column
as a column matrix.
column
as a column matrix.
column
as a column matrix.
column
as a column matrix.
column
as a column matrix.
column
as a column matrix.
column
as a vector.
column
as a vector.
column
as a vector.
column
as a vector.
column
as a vector.
column
as a vector.
report
, and shortReport
.
report
and shortReport
.
report
and shortReport
.
nextCoordinate
or nextCoordinates
will return the values
ui, j, ui, j+1,..., where i is the
index of the current point.
expansionMode
.
XYChart
.
XYChart
.
\documentclass
(and other) commands in the
created LATEX files.
setLambda
with argument 1/mean to change the mean of this distribution.
GammaProcessPCA
and the
BrownianMotionPCA
.
InverseGaussianProcessPCA
and the inner
BrownianMotionPCA
.
InverseGaussianProcess
.
GammaProcess
.
GammaProcess
'es.
BrownianMotionPCA
to ν.
DescriptiveStatistics.getPercentile(double)
.
row
as a row matrix.
row
as a row matrix.
row
as a row matrix.
row
as a row matrix.
row
as a row matrix.
row
as a row matrix.
row
as a row matrix.
row
as a row matrix.
row
as a row matrix.
row
as a row matrix.
row
as a row matrix.
row
as a row matrix.
row
as a row matrix.
row
as a row matrix.
row
as a vector.
row
as a vector.
row
as a vector.
row
as a vector.
row
as a vector.
row
as a vector.
int
seed.
int
array seed.
long
seed.
int
seed.
int
array seed.
long
seed.
int
seed.
int
array seed.
int
seed.
int
array seed.
long
seed.
int
seed.
int
array seed.
long
seed.
waitList
for this bin.
waitList
and servList
for this resource.
RandomStream
to
stream.
RandomStream
to
stream.
RandomStream
to
stream.
RandomStream
used by this generator to stream.
RandomStream
used by this object to stream.
RandomStream
of the GammaGen
to stream.
RandomStream
of the GammaGen
and
the BetaGen
to stream.
RandomStream
of the gamma generator and the
RandomStream
of
the inner BrownianMotionPCA
to
stream.
RandomStream
for the underlying Brownian motion to stream.
InverseGaussianProcess
.
RandomStream
's.
RandomStream
of the two GammaProcess
'es to stream.
row, column
using data in
the input subMatrix
array.
row, column
using data in
the input subMatrix
array.
row, column
using data in
the input subMatrix
array.
row, column
using data in
the input subMatrix
array.
row, column
using data in
the input subMatrix
array.
row, column
using data in
the input subMatrix
array.
row, column
using data in
the input subMatrix
array.
row, column
using data in
the input subMatrix
array.
row, column
using data in
the input subMatrix
array.
row, column
using data in
the input subMatrix
array.
DatasetChangeEvent
to all
registered listeners.
valuesFileURL
using a string URL representation
valuesFileURL
evaluate
for
the undefined function 0/0 to zeroOverZero.
short
elements; implemented with arrays.short
elements; implemented with arrays.shuffle
(byte[], RandomStream).
shuffle
(byte[], RandomStream).
shuffle
(byte[], RandomStream).
shuffle
(byte[], RandomStream).
shuffle
(byte[], RandomStream).
shuffle
(byte[], RandomStream).
shuffle
(byte[], RandomStream).
shuffle
(Object[], n, k, RandomStream).
shuffle
(Object[], n, k, RandomStream).
shuffle
(Object[], n, k, RandomStream).
shuffle
(Object[], n, k, RandomStream).
shuffle
(Object[], n, k, RandomStream).
shuffle
(Object[], n, k, RandomStream).
shuffle
(Object[], n, k, RandomStream).
shuffle
(Object[], n, k, RandomStream).
from
(inclusive) and to
(inclusive).
from
(inclusive) and to
(inclusive).
from
(inclusive) and to
(inclusive).
from
(inclusive) and to
(inclusive).
from
(inclusive) and to
(inclusive).
from
(inclusive) and to
(inclusive).
from
(inclusive) and
to
(inclusive).
from
(inclusive) and to
(inclusive).
from
(inclusive) and to
(inclusive).
from
(inclusive) and to
(inclusive).
from
(inclusive) and to
(inclusive).
from
(inclusive) and to
(inclusive).
from
(inclusive) and to
(inclusive).
from
(inclusive) and to
(inclusive).
from
(inclusive) and to
(inclusive).
from
(inclusive) and to
(inclusive).
from
(inclusive) and to
(inclusive).
from
(inclusive) and to
(inclusive).
from
(inclusive) and to
(inclusive).
from
(inclusive) and to
(inclusive).
from
(inclusive) and to
(inclusive).
from
(inclusive) and to
(inclusive).
from
(inclusive) and to
(inclusive).
from
(inclusive) and to
(inclusive).
from
(inclusive) and to
(inclusive).
from
(inclusive) and to
(inclusive).
from
(inclusive) and to
(inclusive).
from
(inclusive) and to
(inclusive).
from
(inclusive) and to
(inclusive).
from
(inclusive) and to
(inclusive).
from
(inclusive) and to
(inclusive).
from
(inclusive) and to
(inclusive).
from
(inclusive) and to
(inclusive).
from
(inclusive) and to
(inclusive).
from
(inclusive) and to
(inclusive).
x
.
x
.
x
.
x
.
x
.
x
.
FastMath.signum
method wrapped as a ComposableFunction
.
long
elements; implemented with arrays; not efficient; just to demonstrate which methods you must override to implement a fully functional list.long
elements; implemented with arrays;
not efficient; just to demonstrate which methods you must override to
implement a fully functional list.RealConvergenceChecker
interface using
only point coordinates.other constructor
instead.
RealConvergenceChecker
interface using
only objective function values.VectorialConvergenceChecker
interface using
only point coordinates.VectorialConvergenceChecker
interface using
only objective function values.Simulator
static methods.
SimpsonIntegrator.integrate(UnivariateRealFunction, double, double)
method.
FastMath.sin
method wrapped as a ComposableFunction
.
FastMath.sinh
method wrapped as a ComposableFunction
.
Skewness
identical
to the original
BicubicSplineInterpolator
instead. If smoothing is desired, a tentative implementation is provided in class
SmoothingPolynomialBicubicSplineInterpolator
.
This class will be removed in math 3.0.SmpBlas.allocateBlas(int, cern.colt.matrix.linalg.Blas)
.
PointSetRandomization
that performs a striped matrix scrambling and adds a random
digital shift.min
and max
.
startValue
.
UnivariateRealSolver.solve(UnivariateRealFunction, double, double)
since 2.0
UnivariateRealSolver.solve(UnivariateRealFunction, double, double, double)
since 2.0
b
.
b
.
b
.
b
.
b
.
DecompositionSolver.solve(double[])
DecompositionSolver.solve(RealMatrix)
MullerSolver.solve2(UnivariateRealFunction, double, double)
since 2.0
vector
into ascending order.
vector
according to the comparator comp
.
vector
according to the comparator
c
.
vector
into ascending order.
vector
according to the comparator comp
.
vector
according to the comparator
c
.
vector
into ascending order.
vector
according to the comparator
c
.
vector
into ascending order.
vector
according to the comparator
c
.
FieldVector
interface with a OpenIntToFieldHashMap
backing store.RealMatrix
implementations that require sparse backing storageEventList
using a splay tree.FastMath.sqrt
method wrapped as a ComposableFunction
.
this
2 for this complex
number.
StandardDeviation
identical
to the original
isBiasCorrected
property.
isBiasCorrected
property and the supplied external moment.
startInteg
, after initializing the variable
to val.
UserRecord
for this resource.
FJTaskRunnerGroup.stats()
.
FixedStepHandler
into a StepHandler
.start
.
start
.
UnivariateStatistic
with
StorelessUnivariateStatistic.increment(double)
and StorelessUnivariateStatistic.incrementAll(double[])
methods for adding
values and updating internal state.stripedMatrixScramble
except that the
elements on and under the diagonal of each matrix
Mj are
chosen as in leftMatrixScrambleFaurePermut
.
ContinuousDistribution
for
the Student t-distribution
with n degrees of freedom, where n is a positive integer.StudentDist
for
the Student t-distribution.PointSet
object, initially identical to P,
and from which a subset of the points and/or a subset of the coordinates
is to be extracted.
value
for the most recently added value.
text
where any occurence of
token
is replaced by substitute
.
text
where any occurence of
token
is replaced by substitute
.
BinaryFunction
.
BigInteger
from the value of this one,
returning the result in reduced form.
v
from this vector.
v
from this vector.
m
.
m
.
v
from this vector.
v
from this vector.
m
.
m
.
m
.
m
.
m
.
v
from this vector.
v
from this vector.
m
.
v
from this vector.
v
from this vector.
Sum
identical
to the original
Double.NaN
if the array is empty.
Double.NaN
if the designated subarray
is empty.
sum
, and stores
the results into the array s.
Double.NaN
if the array is empty.
Double.NaN
if the designated subarray
is empty.
addValue
method.SumOfLogs
identical
to the original
SumOfSquares
identical
to the original
Double.NaN
if the array is empty.
Double.NaN
if the designated subarray
is empty.
formatp1
to determine
which p-values should be marked as suspect when printing test results.
DescriptiveStatistics
that
is safe to use in a multithreaded environment.MultivariateSummaryStatistics
that
is safe to use in a multithreaded environment.SummaryStatistics
that
is safe to use in a multithreaded environment.AbstractChrono
class to compute
the total system time using Java's builtin System.nanoTime.sampleStats
to mu
.
StatisticalSummary
instances, without the
assumption of equal subpopulation variances.
sampleStats
to mu
.
StatisticalSummary
instances, without the
assumption of equal subpopulation variances.
String
s in different styles.Tally
for which the individual
observations are stored in a list implemented as a
DoubleArrayList
.FastMath.tan
method wrapped as a ComposableFunction
.
FastMath.tanh
method wrapped as a ComposableFunction
.
TDistribution
.ThirdMoment
identical
to the original
AbstractChrono
class to compute the CPU time for a single thread.Thread
variable and initializes it to zero.
ThreadProcessSimulator
variable.
times
times the receiver.
times
times the receiver.
times
times the receiver.
times
times the receiver.
times
times the receiver.
times
times the receiver.
times
times the receiver.
times
times the receiver.
times
times the receiver.
times
times the
receiver.
times
times the
receiver.
times
times the
receiver.
times
times the
receiver.
times
times the
receiver.
times
times the
receiver.
times
times the
receiver.
times
times the
receiver.
times
times the
receiver.
XYChart
.
toLatexCdf
, but for the probability density instead
of the cdf.
toLatexCdf
, but for the probability instead
of the cdf.
java.util.ArrayList
containing all the elements in the receiver.
java.util.ArrayList
containing all the elements in the receiver.
java.util.ArrayList
containing all the elements in the receiver.
java.util.ArrayList
containing all the elements in
the receiver.
java.util.ArrayList
containing all the elements in the receiver.
java.util.ArrayList
containing all the elements in the receiver.
java.util.ArrayList
containing all the elements in the receiver.
java.util.ArrayList
containing all the elements in the receiver.
java.util.ArrayList
containing all the elements in the receiver.
java.util.ArrayList
containing all the elements in the receiver.
java.util.ArrayList
containing all the elements in
the receiver.
java.util.ArrayList
containing all the elements in
the receiver.
java.util.ArrayList
containing all the elements in
the receiver.
java.util.ArrayList
containing all the elements in
the receiver.
java.util.ArrayList
containing all the elements in
the receiver.
java.util.ArrayList
containing all the elements in
the receiver.
java.util.ArrayList
containing all the elements in
the receiver.
java.util.ArrayList
containing all the elements in
the receiver.
java.util.ArrayList
containing all the elements in
the receiver.
String
representing this fraction, ie
"num / dem" or just "num" if the denominator is one.
String
representing this fraction, ie
"num / dem" or just "num" if the denominator is one.
toString
with the associated points.
String
containing all the data of
the BitMatrix.
String
containing all the data of
the DMatrix.
String
.
getLongName
.
TrapezoidIntegrator.integrate(UnivariateRealFunction, double, double)
method.
ContinuousDistribution
for
the triangular distribution with domain [a, b] and mode
(or shape parameter) m, where
a <= m <= b.Tricubic interpolation in three dimensions
F.- TricubicSplineInterpolatingFunction(double[], double[], double[], double[][][], double[][][], double[][][], double[][][], double[][][], double[][][], double[][][], double[][][]) - Constructor for class org.apache.commons.math.analysis.interpolation.TricubicSplineInterpolatingFunction
- TricubicSplineInterpolator - Class in org.apache.commons.math.analysis.interpolation
- Generates a tricubic interpolating function.
- TricubicSplineInterpolator() - Constructor for class org.apache.commons.math.analysis.interpolation.TricubicSplineInterpolator
- trigamma(double) - Static method in class org.apache.commons.math.special.Gamma
- Computes the trigamma function of x.
- trigamma(double) - Static method in class umontreal.iro.lecuyer.util.Num
- Returns the value of the trigamma function dψ(x)/dx, the derivative of the digamma function, evaluated at x.
- Trigonometric - Class in jhplot.math.num.special
- Utility class that provides methods related to the trigonometric functions.
- trim(int, int) - Method in class cern.hep.aida.bin.DynamicBin1D
- Removes the s smallest and l largest elements from the receiver.
- trim(int, int) - Method in class hep.aida.tdouble.bin.DynamicDoubleBin1D
- Removes the s smallest and l largest elements from the receiver.
- trim(int, int) - Method in class hep.aida.tfloat.bin.DynamicFloatBin1D
- Removes the s smallest and l largest elements from the receiver.
- trimmedMean(int, int) - Method in class cern.hep.aida.bin.DynamicBin1D
- Returns the trimmed mean.
- trimmedMean(DoubleArrayList, double, int, int) - Static method in class cern.jet.stat.Descriptive
- Returns the trimmed mean of a sorted data sequence.
- trimmedMean(DoubleArrayList, double, int, int) - Static method in class cern.jet.stat.tdouble.DoubleDescriptive
- Returns the trimmed mean of a sorted data sequence.
- trimmedMean(FloatArrayList, float, int, int) - Static method in class cern.jet.stat.tfloat.FloatDescriptive
- Returns the trimmed mean of a sorted data sequence.
- trimmedMean(int, int) - Method in class hep.aida.tdouble.bin.DynamicDoubleBin1D
- Returns the trimmed mean.
- trimmedMean(int, int) - Method in class hep.aida.tfloat.bin.DynamicFloatBin1D
- Returns the trimmed mean.
- trimToCapacity(byte[], int) - Static method in class cern.colt.Arrays
- Ensures that the specified array cannot hold more than maxCapacity elements.
- trimToCapacity(char[], int) - Static method in class cern.colt.Arrays
- Ensures that the specified array cannot hold more than maxCapacity elements.
- trimToCapacity(double[], int) - Static method in class cern.colt.Arrays
- Ensures that the specified array cannot hold more than maxCapacity elements.
- trimToCapacity(float[], int) - Static method in class cern.colt.Arrays
- Ensures that the specified array cannot hold more than maxCapacity elements.
- trimToCapacity(int[], int) - Static method in class cern.colt.Arrays
- Ensures that the specified array cannot hold more than maxCapacity elements.
- trimToCapacity(long[], int) - Static method in class cern.colt.Arrays
- Ensures that the specified array cannot hold more than maxCapacity elements.
- trimToCapacity(Object[], int) - Static method in class cern.colt.Arrays
- Ensures that the specified array cannot hold more than maxCapacity elements.
- trimToCapacity(short[], int) - Static method in class cern.colt.Arrays
- Ensures that the specified array cannot hold more than maxCapacity elements.
- trimToCapacity(boolean[], int) - Static method in class cern.colt.Arrays
- Ensures that the specified array cannot hold more than maxCapacity elements.
- trimToSize() - Method in class cern.colt.list.AbstractList
- Trims the capacity of the receiver to be the receiver's current size.
- trimToSize() - Method in class cern.colt.list.BooleanArrayList
- Trims the capacity of the receiver to be the receiver's current size.
- trimToSize() - Method in class cern.colt.list.ByteArrayList
- Trims the capacity of the receiver to be the receiver's current size.
- trimToSize() - Method in class cern.colt.list.CharArrayList
- Trims the capacity of the receiver to be the receiver's current size.
- trimToSize() - Method in class cern.colt.list.DistinctNumberList
- Trims the capacity of the receiver to be the receiver's current size.
- trimToSize() - Method in class cern.colt.list.DoubleArrayList
- Trims the capacity of the receiver to be the receiver's current size.
- trimToSize() - Method in class cern.colt.list.FloatArrayList
- Trims the capacity of the receiver to be the receiver's current size.
- trimToSize() - Method in class cern.colt.list.IntArrayList
- Trims the capacity of the receiver to be the receiver's current size.
- trimToSize() - Method in class cern.colt.list.LongArrayList
- Trims the capacity of the receiver to be the receiver's current size.
- trimToSize() - Method in class cern.colt.list.MinMaxNumberList
- Trims the capacity of the receiver to be the receiver's current size.
- trimToSize() - Method in class cern.colt.list.ObjectArrayList
- Trims the capacity of the receiver to be the receiver's current size.
- trimToSize() - Method in class cern.colt.list.ShortArrayList
- Trims the capacity of the receiver to be the receiver's current size.
- trimToSize() - Method in class cern.colt.list.SimpleLongArrayList
- Trims the capacity of the receiver to be the receiver's current size.
- trimToSize() - Method in class cern.colt.list.tboolean.BooleanArrayList
- Trims the capacity of the receiver to be the receiver's current size.
- trimToSize() - Method in class cern.colt.list.tbyte.ByteArrayList
- Trims the capacity of the receiver to be the receiver's current size.
- trimToSize() - Method in class cern.colt.list.tchar.CharArrayList
- Trims the capacity of the receiver to be the receiver's current size.
- trimToSize() - Method in class cern.colt.list.tdouble.DoubleArrayList
- Trims the capacity of the receiver to be the receiver's current size.
- trimToSize() - Method in class cern.colt.list.tfloat.FloatArrayList
- Trims the capacity of the receiver to be the receiver's current size.
- trimToSize() - Method in class cern.colt.list.tint.IntArrayList
- Trims the capacity of the receiver to be the receiver's current size.
- trimToSize() - Method in class cern.colt.list.tlong.DistinctNumberList
- Trims the capacity of the receiver to be the receiver's current size.
- trimToSize() - Method in class cern.colt.list.tlong.LongArrayList
- Trims the capacity of the receiver to be the receiver's current size.
- trimToSize() - Method in class cern.colt.list.tlong.MinMaxNumberList
- Trims the capacity of the receiver to be the receiver's current size.
- trimToSize() - Method in class cern.colt.list.tlong.SimpleLongArrayList
- Trims the capacity of the receiver to be the receiver's current size.
- trimToSize() - Method in class cern.colt.list.tobject.ObjectArrayList
- Trims the capacity of the receiver to be the receiver's current size.
- trimToSize() - Method in class cern.colt.list.tshort.ShortArrayList
- Trims the capacity of the receiver to be the receiver's current size.
- trimToSize() - Method in class cern.colt.map.AbstractMap
- Trims the capacity of the receiver to be the receiver's current size.
- trimToSize() - Method in class cern.colt.map.OpenDoubleIntHashMap
- Trims the capacity of the receiver to be the receiver's current size.
- trimToSize() - Method in class cern.colt.map.OpenIntDoubleHashMap
- Trims the capacity of the receiver to be the receiver's current size.
- trimToSize() - Method in class cern.colt.map.OpenIntIntHashMap
- Trims the capacity of the receiver to be the receiver's current size.
- trimToSize() - Method in class cern.colt.map.OpenIntObjectHashMap
- Trims the capacity of the receiver to be the receiver's current size.
- trimToSize() - Method in class cern.colt.map.OpenLongObjectHashMap
- Trims the capacity of the receiver to be the receiver's current size.
- trimToSize() - Method in class cern.colt.map.tdouble.OpenDoubleIntHashMap
- Trims the capacity of the receiver to be the receiver's current size.
- trimToSize() - Method in class cern.colt.map.tdouble.OpenDoubleLongHashMap
- Trims the capacity of the receiver to be the receiver's current size.
- trimToSize() - Method in class cern.colt.map.tdouble.OpenIntDoubleHashMap
- Trims the capacity of the receiver to be the receiver's current size.
- trimToSize() - Method in class cern.colt.map.tdouble.OpenLongDoubleHashMap
- Trims the capacity of the receiver to be the receiver's current size.
- trimToSize() - Method in class cern.colt.map.tfloat.OpenFloatIntHashMap
- Trims the capacity of the receiver to be the receiver's current size.
- trimToSize() - Method in class cern.colt.map.tfloat.OpenFloatLongHashMap
- Trims the capacity of the receiver to be the receiver's current size.
- trimToSize() - Method in class cern.colt.map.tfloat.OpenIntFloatHashMap
- Trims the capacity of the receiver to be the receiver's current size.
- trimToSize() - Method in class cern.colt.map.tfloat.OpenLongFloatHashMap
- Trims the capacity of the receiver to be the receiver's current size.
- trimToSize() - Method in class cern.colt.map.tint.OpenIntIntHashMap
- Trims the capacity of the receiver to be the receiver's current size.
- trimToSize() - Method in class cern.colt.map.tlong.OpenIntLongHashMap
- Trims the capacity of the receiver to be the receiver's current size.
- trimToSize() - Method in class cern.colt.map.tlong.OpenLongIntHashMap
- Trims the capacity of the receiver to be the receiver's current size.
- trimToSize() - Method in class cern.colt.map.tlong.OpenLongLongHashMap
- Trims the capacity of the receiver to be the receiver's current size.
- trimToSize() - Method in class cern.colt.map.tobject.OpenIntObjectHashMap
- Trims the capacity of the receiver to be the receiver's current size.
- trimToSize() - Method in class cern.colt.map.tobject.OpenLongObjectHashMap
- Trims the capacity of the receiver to be the receiver's current size.
- trimToSize() - Method in class cern.colt.matrix.AbstractMatrix
- Releases any superfluous internal memory.
- trimToSize() - Method in class cern.colt.matrix.impl.AbstractMatrix
- Releases any superfluous internal memory.
- trimToSize() - Method in class cern.colt.matrix.impl.RCDoubleMatrix2D
- trimToSize() - Method in class cern.colt.matrix.impl.SparseDoubleMatrix1D
- Releases any superfluous memory created by explicitly putting zero values into cells formerly having non-zero values; An application can use this operation to minimize the storage of the receiver.
- trimToSize() - Method in class cern.colt.matrix.impl.SparseDoubleMatrix2D
- Releases any superfluous memory created by explicitly putting zero values into cells formerly having non-zero values; An application can use this operation to minimize the storage of the receiver.
- trimToSize() - Method in class cern.colt.matrix.impl.SparseDoubleMatrix3D
- Releases any superfluous memory created by explicitly putting zero values into cells formerly having non-zero values; An application can use this operation to minimize the storage of the receiver.
- trimToSize() - Method in class cern.colt.matrix.impl.SparseObjectMatrix1D
- Releases any superfluous memory created by explicitly putting zero values into cells formerly having non-zero values; An application can use this operation to minimize the storage of the receiver.
- trimToSize() - Method in class cern.colt.matrix.impl.SparseObjectMatrix2D
- Releases any superfluous memory created by explicitly putting zero values into cells formerly having non-zero values; An application can use this operation to minimize the storage of the receiver.
- trimToSize() - Method in class cern.colt.matrix.impl.SparseObjectMatrix3D
- Releases any superfluous memory created by explicitly putting zero values into cells formerly having non-zero values; An application can use this operation to minimize the storage of the receiver.
- trimToSize() - Method in class cern.colt.matrix.tdcomplex.impl.SparseCCDComplexMatrix2D
- trimToSize() - Method in class cern.colt.matrix.tdcomplex.impl.SparseCCMDComplexMatrix2D
- trimToSize() - Method in class cern.colt.matrix.tdcomplex.impl.SparseRCDComplexMatrix2D
- trimToSize() - Method in class cern.colt.matrix.tdcomplex.impl.SparseRCMDComplexMatrix2D
- trimToSize() - Method in class cern.colt.matrix.tdouble.impl.SparseCCDoubleMatrix2D
- trimToSize() - Method in class cern.colt.matrix.tdouble.impl.SparseCCMDoubleMatrix2D
- trimToSize() - Method in class cern.colt.matrix.tdouble.impl.SparseDoubleMatrix1D
- trimToSize() - Method in class cern.colt.matrix.tdouble.impl.SparseDoubleMatrix2D
- trimToSize() - Method in class cern.colt.matrix.tdouble.impl.SparseDoubleMatrix3D
- trimToSize() - Method in class cern.colt.matrix.tdouble.impl.SparseRCDoubleMatrix2D
- trimToSize() - Method in class cern.colt.matrix.tdouble.impl.SparseRCMDoubleMatrix2D
- trimToSize() - Method in class cern.colt.matrix.tfcomplex.impl.SparseCCFComplexMatrix2D
- trimToSize() - Method in class cern.colt.matrix.tfcomplex.impl.SparseCCMFComplexMatrix2D
- trimToSize() - Method in class cern.colt.matrix.tfcomplex.impl.SparseRCFComplexMatrix2D
- trimToSize() - Method in class cern.colt.matrix.tfcomplex.impl.SparseRCMFComplexMatrix2D
- trimToSize() - Method in class cern.colt.matrix.tfloat.impl.SparseCCFloatMatrix2D
- trimToSize() - Method in class cern.colt.matrix.tfloat.impl.SparseCCMFloatMatrix2D
- trimToSize() - Method in class cern.colt.matrix.tfloat.impl.SparseFloatMatrix1D
- trimToSize() - Method in class cern.colt.matrix.tfloat.impl.SparseFloatMatrix2D
- trimToSize() - Method in class cern.colt.matrix.tfloat.impl.SparseFloatMatrix3D
- trimToSize() - Method in class cern.colt.matrix.tfloat.impl.SparseRCFloatMatrix2D
- trimToSize() - Method in class cern.colt.matrix.tfloat.impl.SparseRCMFloatMatrix2D
- trimToSize() - Method in class cern.colt.matrix.tint.impl.SparseCCIntMatrix2D
- trimToSize() - Method in class cern.colt.matrix.tint.impl.SparseCCMIntMatrix2D
- trimToSize() - Method in class cern.colt.matrix.tint.impl.SparseIntMatrix1D
- trimToSize() - Method in class cern.colt.matrix.tint.impl.SparseIntMatrix2D
- trimToSize() - Method in class cern.colt.matrix.tint.impl.SparseIntMatrix3D
- trimToSize() - Method in class cern.colt.matrix.tint.impl.SparseRCIntMatrix2D
- trimToSize() - Method in class cern.colt.matrix.tint.impl.SparseRCMIntMatrix2D
- trimToSize() - Method in class cern.colt.matrix.tlong.impl.SparseCCLongMatrix2D
- trimToSize() - Method in class cern.colt.matrix.tlong.impl.SparseCCMLongMatrix2D
- trimToSize() - Method in class cern.colt.matrix.tlong.impl.SparseLongMatrix1D
- trimToSize() - Method in class cern.colt.matrix.tlong.impl.SparseLongMatrix2D
- trimToSize() - Method in class cern.colt.matrix.tlong.impl.SparseLongMatrix3D
- trimToSize() - Method in class cern.colt.matrix.tlong.impl.SparseRCLongMatrix2D
- trimToSize() - Method in class cern.colt.matrix.tlong.impl.SparseRCMLongMatrix2D
- trimToSize() - Method in class cern.colt.matrix.tobject.impl.SparseCCMObjectMatrix2D
- trimToSize() - Method in class cern.colt.matrix.tobject.impl.SparseCCObjectMatrix2D
- trimToSize() - Method in class cern.colt.matrix.tobject.impl.SparseObjectMatrix1D
- Releases any superfluous memory created by explicitly putting zero values into cells formerly having non-zero values; An application can use this operation to minimize the storage of the receiver.
- trimToSize() - Method in class cern.colt.matrix.tobject.impl.SparseObjectMatrix2D
- Releases any superfluous memory created by explicitly putting zero values into cells formerly having non-zero values; An application can use this operation to minimize the storage of the receiver.
- trimToSize() - Method in class cern.colt.matrix.tobject.impl.SparseObjectMatrix3D
- Releases any superfluous memory created by explicitly putting zero values into cells formerly having non-zero values; An application can use this operation to minimize the storage of the receiver.
- trimToSize() - Method in class cern.colt.matrix.tobject.impl.SparseRCMObjectMatrix2D
- trimToSize() - Method in class cern.colt.matrix.tobject.impl.SparseRCObjectMatrix2D
- trimToSize() - Method in class cern.hep.aida.bin.AbstractBin
- Trims the capacity of the receiver to be the receiver's current size.
- trimToSize() - Method in class cern.hep.aida.bin.AbstractBin1D
- Trims the capacity of the receiver to be the receiver's current size.
- trimToSize() - Method in class cern.hep.aida.bin.DynamicBin1D
- Trims the capacity of the receiver to be the receiver's current size.
- trimToSize() - Method in class hep.aida.tdouble.bin.AbstractDoubleBin
- Trims the capacity of the receiver to be the receiver's current size.
- trimToSize() - Method in class hep.aida.tdouble.bin.AbstractDoubleBin1D
- Trims the capacity of the receiver to be the receiver's current size.
- trimToSize() - Method in class hep.aida.tdouble.bin.DynamicDoubleBin1D
- Trims the capacity of the receiver to be the receiver's current size.
- trimToSize() - Method in class hep.aida.tfloat.bin.AbstractFloatBin
- Trims the capacity of the receiver to be the receiver's current size.
- trimToSize() - Method in class hep.aida.tfloat.bin.AbstractFloatBin1D
- Trims the capacity of the receiver to be the receiver's current size.
- trimToSize() - Method in class hep.aida.tfloat.bin.DynamicFloatBin1D
- Trims the capacity of the receiver to be the receiver's current size.
- trinitySunday() - Method in class flanagan.math.TimeAndDate
- trinitySunday(int) - Method in class flanagan.math.TimeAndDate
- triplePartition(double[], double[], double[], int, int, double[], int, int, int[]) - Static method in class cern.colt.Partitioning
- Same as
Partitioning.triplePartition(int[],int[],int[],int,int,int[],int,int,int[])
except that it synchronously partitions double[] rather than int[] arrays.- triplePartition(double[], double[], double[], int, int, double) - Static method in class cern.colt.Partitioning
- Same as
Partitioning.triplePartition(int[],int[],int[],int,int,int)
except that it synchronously partitions double[] rather than int[] arrays.- triplePartition(int[], int[], int[], int, int, int[], int, int, int[]) - Static method in class cern.colt.Partitioning
- Same as
Partitioning.partition(int[],int,int,int[],int,int,int[])
except that this method synchronously partitions three arrays at the same time; all three arrays are partially sorted according to the elements of the primary array.- triplePartition(int[], int[], int[], int, int, int) - Static method in class cern.colt.Partitioning
- Same as
Partitioning.partition(int[],int,int,int)
except that this method synchronously partitions three arrays at the same time; all three arrays are partially sorted according to the elements of the primary array.- TrivariateRealFunction - Interface in org.apache.commons.math.analysis
- An interface representing a trivariate real function.
- TrivariateRealGridInterpolator - Interface in org.apache.commons.math.analysis.interpolation
- Interface representing a trivariate real interpolating function where the sample points must be specified on a regular grid.
- trueSampleNumber() - Method in class flanagan.analysis.Stat
- trueSampleNumber_as_BigDecimal() - Method in class flanagan.analysis.Stat
- trueSampleNumber_as_Complex() - Method in class flanagan.analysis.Stat
- trueSampleNumber_as_double() - Method in class flanagan.analysis.Stat
- trueSampleNumber_as_int() - Method in class flanagan.analysis.Stat
- truncate(ErrorProp, int) - Static method in class flanagan.analysis.ErrorProp
- truncate(int) - Method in class flanagan.analysis.ErrorProp
- truncate(int) - Method in class flanagan.analysis.Stat
- truncate(int) - Method in class flanagan.math.ArrayMaths
- truncate(double, int) - Static method in class flanagan.math.Fmath
- truncate(float, int) - Static method in class flanagan.math.Fmath
- TruncatedDist - Class in umontreal.iro.lecuyer.probdist
- This container class takes an arbitrary continuous distribution and truncates it to an interval [a, b], where a and b can be finite or infinite.
- TruncatedDist(ContinuousDistribution, double, double) - Constructor for class umontreal.iro.lecuyer.probdist.TruncatedDist
- Constructs a new distribution by truncating distribution dist to the interval [a, b].
- TruncatedRandomStream - Class in umontreal.iro.lecuyer.rng
- Represents a container random stream generating numbers in an interval (a, b) instead of in (0, 1), where 0 <= a < b <= 1, by using the contained stream.
- TruncatedRandomStream(RandomStream, double, double) - Constructor for class umontreal.iro.lecuyer.rng.TruncatedRandomStream
- tsallisEntropyNat(double) - Method in class flanagan.analysis.Stat
- tsallisEntropyNat(double[], double) - Static method in class flanagan.analysis.Stat
- tTest(double, double[], double) - Static method in class org.apache.commons.math.stat.inference.TestUtils
- tTest(double, double[]) - Static method in class org.apache.commons.math.stat.inference.TestUtils
- tTest(double, StatisticalSummary, double) - Static method in class org.apache.commons.math.stat.inference.TestUtils
- tTest(double, StatisticalSummary) - Static method in class org.apache.commons.math.stat.inference.TestUtils
- tTest(double[], double[], double) - Static method in class org.apache.commons.math.stat.inference.TestUtils
- tTest(double[], double[]) - Static method in class org.apache.commons.math.stat.inference.TestUtils
- tTest(StatisticalSummary, StatisticalSummary, double) - Static method in class org.apache.commons.math.stat.inference.TestUtils
- tTest(StatisticalSummary, StatisticalSummary) - Static method in class org.apache.commons.math.stat.inference.TestUtils
- TTest - Interface in org.apache.commons.math.stat.inference
- An interface for Student's t-tests.
- tTest(double, double[]) - Method in interface org.apache.commons.math.stat.inference.TTest
- Returns the observed significance level, or p-value, associated with a one-sample, two-tailed t-test comparing the mean of the input array with the constant
mu
.- tTest(double, double[], double) - Method in interface org.apache.commons.math.stat.inference.TTest
- Performs a two-sided t-test evaluating the null hypothesis that the mean of the population from which
sample
is drawn equalsmu
.- tTest(double, StatisticalSummary) - Method in interface org.apache.commons.math.stat.inference.TTest
- Returns the observed significance level, or p-value, associated with a one-sample, two-tailed t-test comparing the mean of the dataset described by
sampleStats
with the constantmu
.- tTest(double, StatisticalSummary, double) - Method in interface org.apache.commons.math.stat.inference.TTest
- Performs a two-sided t-test evaluating the null hypothesis that the mean of the population from which the dataset described by
stats
is drawn equalsmu
.- tTest(double[], double[]) - Method in interface org.apache.commons.math.stat.inference.TTest
- Returns the observed significance level, or p-value, associated with a two-sample, two-tailed t-test comparing the means of the input arrays.
- tTest(double[], double[], double) - Method in interface org.apache.commons.math.stat.inference.TTest
- Performs a two-sided t-test evaluating the null hypothesis that
sample1
andsample2
are drawn from populations with the same mean, with significance levelalpha
.- tTest(StatisticalSummary, StatisticalSummary) - Method in interface org.apache.commons.math.stat.inference.TTest
- Returns the observed significance level, or p-value, associated with a two-sample, two-tailed t-test comparing the means of the datasets described by two StatisticalSummary instances.
- tTest(StatisticalSummary, StatisticalSummary, double) - Method in interface org.apache.commons.math.stat.inference.TTest
- Performs a two-sided t-test evaluating the null hypothesis that
sampleStats1
andsampleStats2
describe datasets drawn from populations with the same mean, with significance levelalpha
.- tTest(double, double[]) - Method in class org.apache.commons.math.stat.inference.TTestImpl
- Returns the observed significance level, or p-value, associated with a one-sample, two-tailed t-test comparing the mean of the input array with the constant
mu
.- tTest(double, double[], double) - Method in class org.apache.commons.math.stat.inference.TTestImpl
- Performs a two-sided t-test evaluating the null hypothesis that the mean of the population from which
sample
is drawn equalsmu
.- tTest(double, StatisticalSummary) - Method in class org.apache.commons.math.stat.inference.TTestImpl
- Returns the observed significance level, or p-value, associated with a one-sample, two-tailed t-test comparing the mean of the dataset described by
sampleStats
with the constantmu
.- tTest(double, StatisticalSummary, double) - Method in class org.apache.commons.math.stat.inference.TTestImpl
- Performs a two-sided t-test evaluating the null hypothesis that the mean of the population from which the dataset described by
stats
is drawn equalsmu
.- tTest(double[], double[]) - Method in class org.apache.commons.math.stat.inference.TTestImpl
- Returns the observed significance level, or p-value, associated with a two-sample, two-tailed t-test comparing the means of the input arrays.
- tTest(double[], double[], double) - Method in class org.apache.commons.math.stat.inference.TTestImpl
- Performs a two-sided t-test evaluating the null hypothesis that
sample1
andsample2
are drawn from populations with the same mean, with significance levelalpha
.- tTest(StatisticalSummary, StatisticalSummary) - Method in class org.apache.commons.math.stat.inference.TTestImpl
- Returns the observed significance level, or p-value, associated with a two-sample, two-tailed t-test comparing the means of the datasets described by two StatisticalSummary instances.
- tTest(StatisticalSummary, StatisticalSummary, double) - Method in class org.apache.commons.math.stat.inference.TTestImpl
- Performs a two-sided t-test evaluating the null hypothesis that
sampleStats1
andsampleStats2
describe datasets drawn from populations with the same mean, with significance levelalpha
.- TTestImpl - Class in org.apache.commons.math.stat.inference
- Implements t-test statistics defined in the
TTest
interface.- TTestImpl() - Constructor for class org.apache.commons.math.stat.inference.TTestImpl
- Default constructor.
- TTestImpl(TDistribution) - Constructor for class org.apache.commons.math.stat.inference.TTestImpl
- Deprecated. in 2.2 (to be removed in 3.0).
- tuple(int) - Method in class hep.aida.ref.tuple.AbstractTuple
- tuple(int) - Method in interface hep.aida.ref.tuple.FTuple
- tuple(int) - Method in class hep.aida.ref.tuple.FTupleAdapter
- Tuple - Class in hep.aida.ref.tuple
- Tuple(String, String, String[], Class[], String) - Constructor for class hep.aida.ref.tuple.Tuple
- Tuple(String, String, String, String) - Constructor for class hep.aida.ref.tuple.Tuple
- Tuple.TupleColumnFactory - Class in hep.aida.ref.tuple
- Tuple.TupleColumnFactory() - Constructor for class hep.aida.ref.tuple.Tuple.TupleColumnFactory
- TupleColumn - Class in hep.aida.ref.tuple
- TupleColumn.TupleColumnBoolean - Class in hep.aida.ref.tuple
- TupleColumn.TupleColumnByte - Class in hep.aida.ref.tuple
- TupleColumn.TupleColumnChar - Class in hep.aida.ref.tuple
- TupleColumn.TupleColumnDouble - Class in hep.aida.ref.tuple
- TupleColumn.TupleColumnFloat - Class in hep.aida.ref.tuple
- TupleColumn.TupleColumnFolder - Class in hep.aida.ref.tuple
- TupleColumn.TupleColumnInt - Class in hep.aida.ref.tuple
- TupleColumn.TupleColumnLong - Class in hep.aida.ref.tuple
- TupleColumn.TupleColumnObject - Class in hep.aida.ref.tuple
- TupleColumn.TupleColumnShort - Class in hep.aida.ref.tuple
- TupleColumn.TupleColumnString - Class in hep.aida.ref.tuple
- TupleCursor - Class in hep.aida.ref.tuple
- TupleCursor(int, int, boolean) - Constructor for class hep.aida.ref.tuple.TupleCursor
- TupleEvent - Class in hep.aida.ref.tuple
- TupleEvent(Object) - Constructor for class hep.aida.ref.tuple.TupleEvent
- TupleFactory - Class in hep.aida.ref.tuple
- TupleFactory(ITree) - Constructor for class hep.aida.ref.tuple.TupleFactory
- twelfthJuly() - Method in class flanagan.math.TimeAndDate
- twelfthJuly(int) - Method in class flanagan.math.TimeAndDate
- TWELVE - Static variable in class cern.colt.matrix.linalg.Property
- A Property object with tolerance()==1.0E-12.
- TWELVE - Static variable in class cern.colt.matrix.tdcomplex.algo.DComplexProperty
- A Property object with tolerance()==1.0E-12.
- TWELVE - Static variable in class cern.colt.matrix.tdouble.algo.DoubleProperty
- A Property object with tolerance()==1.0E-12.
- TWO - Static variable in class org.apache.commons.math.fraction.BigFraction
- A fraction representing "2 / 1".
- TWO - Static variable in class org.apache.commons.math.fraction.Fraction
- A fraction representing "2 / 1".
- TWO_FIFTHS - Static variable in class org.apache.commons.math.fraction.BigFraction
- A fraction representing "2/5".
- TWO_FIFTHS - Static variable in class org.apache.commons.math.fraction.Fraction
- A fraction representing "2/5".
- TWO_PI - Static variable in class org.apache.commons.math.util.MathUtils
- 2 π.
- TWO_QUARTERS - Static variable in class org.apache.commons.math.fraction.BigFraction
- A fraction representing "2/4".
- TWO_QUARTERS - Static variable in class org.apache.commons.math.fraction.Fraction
- A fraction representing "2/4".
- TWO_THIRDS - Static variable in class org.apache.commons.math.fraction.BigFraction
- A fraction representing "2/3".
- TWO_THIRDS - Static variable in class org.apache.commons.math.fraction.Fraction
- A fraction representing "2/3".
- twoBodyDecay(HEParticle, HEParticle, boolean) - Method in class hephysics.particle.HEParticle
- Evaluates 4-vector of decay product in the rest frame of parent.
- twoBodyDecay(LParticle, LParticle, boolean) - Method in class hephysics.particle.LParticle
- Evaluates 4-vector of decay product in the rest frame of parent.
- twoDarray(int, int) - Static method in class flanagan.analysis.ErrorProp
- twoDarray(int, int, double, double) - Static method in class flanagan.analysis.ErrorProp
- twoDarray(int, int, ErrorProp) - Static method in class flanagan.analysis.ErrorProp
- twoDarray(int, int) - Static method in class jhplot.math.ValueErr
- Create a two dimensional array of ValueErr objects of dimensions n and m with zeros
- TWOEXP - Static variable in class umontreal.iro.lecuyer.util.Num
- Contains the precomputed positive powers of 2.
- twopi - Static variable in class cern.clhep.PhysicalConstants
- twopi_mc2_rcl2 - Static variable in class cern.clhep.PhysicalConstants
- type() - Method in class hep.aida.ref.function.Range
- Get the IRange type.
- type() - Method in class hep.aida.ref.GenericFactory
- type() - Method in class hep.aida.ref.ManagedObject
- type() - Method in class hep.aida.ref.tree.Folder
- type() - Method in class hep.aida.ref.tree.Link
- type() - Method in class hep.aida.ref.tree.MountPoint
- type() - Method in class hep.aida.ref.tuple.AbstractTuple.AbstractTupleColumnFactory.BaseTupleColumn
- type() - Method in class hep.aida.ref.tuple.AbstractTuple.AbstractTupleColumnFactory.ITupleTupleColumn
- type() - Method in interface hep.aida.ref.tuple.FTupleColumn
- type() - Method in class hep.aida.ref.tuple.TupleColumn
- type - Variable in class umontreal.iro.lecuyer.charts.CustomHistogramDataset
- The histogram type.
- typeForClass(Class) - Static method in class hep.aida.ref.ManagedObject
- typeIndex() - Method in class flanagan.math.ArrayMaths
FastMath.ulp
method wrapped as a ComposableFunction
.
RandomVectorGenerator
that generates vectors with uncorrelated
components.MersenneTwister
seeded with the given seed.
ContinuousDistribution
for
the uniform distribution
over the interval [a, b].DiscreteDistributionInt
for
the discrete uniform distribution over the range [i, j].MersenneTwister
),
in order to generate the individual components.
UnivariateRealSolver
instances.UnivariateRealSolverFactory
.UnivariateRealSolver
objects.UnuranContinuous
(s, s, genStr).
UnuranDiscreteInt
(s, s, genStr).
UnuranEmpirical
(s, s, dist, genStr).
UnuranEmpirical
(s, aux, genStr), but reading
the observations from the empirical distribution dist.
update
.
Resource
or for Bin
tokens,
or when a process waits for a Condition
.valueOf
(cls, name),
with case insensitive field name look-up.
isBiasCorrected
property.
isBiasCorrected
property
isBiasCorrected
property and the supplied external second moment.
Variance
identical
to the original
Double.NaN
if the array is empty.
Double.NaN
if the designated subarray
is empty.
GammaProcess
objects for
Γ+ and
Γ- are
set to those of and their
initial values
Γ+(t0) and
Γ-(t0) are set to t0.
VarianceGammaProcessDiff
, but the two inner
GammaProcess
'es are of PCA type.VarianceGammaProcessDiffPCA
with
parameters
θ = VarianceGammaProcessDiffPCA
with
parameters
θ = VarianceGammaProcessDiff
, but the two
inner GammaProcess
'es are of the type PCABridge.VarianceGammaProcessDiffPCABridge
with
parameters
θ = VarianceGammaProcessDiff
, but the two
inner GammaProcess
'es are of the PCASymmetricalBridge type.VarianceGammaProcessDiffPCASymmetricalBridge
with
parameters
θ = optimization algorithm
has converged.viewCdf
above.
viewCdf
, but for the probability density instead
of the cdf.
viewProb
above.
UserRecord
for the processes waiting for tokens from this bin.
UserRecord
for the processes waiting for this condition.
UserRecord
objects
for the processes in the waiting list for this resource.
ContinuousDistribution
for the
Watson G distribution (see).ContinuousDistribution
for the
Watson U distribution (see).ContinuousDistribution
for
the Weibull distribution with shape parameter
α > 0, location parameter δ, and scale parameter
λ > 0.WeibullDistribution
.curve fitting
.RandomStream
interface via inheritance from
RandomStreamBase
.RandomStream
interface via inheritance from
RandomStreamBase
.RandomStream
interface via inheritance
from RandomStreamBase
.SSJXYSeriesCollection
.XYLineChart
.XYListSeriesCollection
.Property.ZERO
attached for tolerance.
DoubleProperty.ZERO
attached for
tolerance.
DoubleProperty.ZERO
attached for
tolerance.
FloatProperty.ZERO
attached for
tolerance.
FloatProperty.ZERO
attached for
tolerance.
ZipfDistribution
.
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