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boolean
elements; abstract.byte
elements; abstract.char
elements; abstract.int
, float
, etc.double
elements; abstract.float
elements; abstract.int
elements; abstract.int
, float
, etc.long
elements; abstract.int
, float
, etc.int
, float
, etc.int
, double
, etc.int
, double
, etc.int
, double
, etc.RandomGenerator
interface.short
elements; abstract.StorelessUnivariateStatistic
interface.UnivariateStatistic
interface.m
.
m
.
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.
data
.
DoubleMatrix2D
; concentrates most functionality of this package.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.
BigMatrix
using a BigDecimal[][] array to store entries
and
LU decompostion to support linear system
solution and inverse.data
as the underlying
data array.
data
as the underlying
data array.
data
as the underlying data array.
v
as the
data for the unique column of the v.length x 1
matrix
created.
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.
BinomialDistribution
.boolean
elements; implemented with arrays. 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.
byte
elements; implemented with arrays.CauchyDistribution
.long >= value
.
cern.colt.matrix
, without subsetting or supersetting.DoubleMatrix2D
and DoubleMatrix1D
.char
elements; implemented with arrays.observed
and expected
freqeuncy counts.
counts
array, viewed as a two-way table.
ChiSquaredDistribution
observed
frequency counts to those in the expected
array.
alpha
.
counts
array, viewed as a two-way table.
alpha
.
ChiSquareTest
interface.AbstractRandomGenerator.nextGaussian()
.
BitMatrix
produces a new BitMatrix
that is equal to it.
BitVector
produces a new BitVector
that is equal to it.
valuesFileURL
after use in REPLAY_MODE.
Complex
-valued functions.valuesFileURL
, using the default number of bins.
valuesFileURL
and binCount
bins.
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.
Random
using the supplied
RandomGenerator
.
dimension x dimension
identity matrix.
BigMatrix
whose entries are the the values in the
the input array.
BigMatrix
whose entries are the the values in the
the input array.
BigMatrix
whose entries are the the values in the
the input array.
BigMatrix
using the data from the input
array.
BigMatrix
using the data from the input
array.
BigMatrix
using the data from the input
array.
RealMatrix
using the data from the input
array.
dimension x dimension
identity matrix.
RealMatrix
whose entries are the the values in the
the input array.
BigMatrix
using the data from the input
array.
BigMatrix
using the data from the input
array.
BigMatrix
using the data from the input
array.
RealMatrix
using the data from the input
array.
x
).
x
).
x
).
x
).
Property.DEFAULT
attached for tolerance.
DescriptiveStatistics
.UnivariateRealFunction
representing a differentiable univariate real function.i initial elements of the array.
- DiscreteDistribution - Interface in org.apache.commons.math.distribution
- Base interface for discrete distributions.
- display() -
Method in class cern.colt.Timer
- Prints the elapsed time on System.out
- disposeMe() -
Method in class jhplot.GHMargin
- Dippose 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(DataPoint, DataPoint) -
Static method in class jminhep.cluster.DataPoint
- Returns the distance between two data points
- 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.
- Distribution - Interface in org.apache.commons.math.distribution
- Base interface for probability distributions.
- DistributionFactory - Class in org.apache.commons.math.distribution
- This factory provids the means to create common statistical distributions.
- DistributionFactoryImpl - Class in org.apache.commons.math.distribution
- A concrete distribution factory.
- DistributionFactoryImpl() -
Constructor for class org.apache.commons.math.distribution.DistributionFactoryImpl
- Default constructor.
- 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.
- distroy() -
Method in class jhplot.HChart
- Distroy the canvas frame
- distroy() -
Method in class jhplot.HGraph
- Distroy the canvas frame
- distroy() -
Method in class jhplot.HPlot
- Distroy the canvas frame
- distroy() -
Method in class jhplot.HPlot3D
- Distroy the canvas
- 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(Binner1D, Binner1D, Binner1D) -
Static method in class hep.aida.ref.histogram.binner.BinnerMath
-
- 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(Complex) -
Method in class org.apache.commons.math.complex.Complex
- Return the quotient of this complex number and the given complex number.
- divide(Fraction) -
Method in class org.apache.commons.math.fraction.Fraction
- Divide the value of this fraction by another.
- 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
-
- Double27Function - Interface in cern.colt.function
- 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.
- Double9Function - Interface in cern.colt.function
- Interface that represents a function object: a function that takes
9 arguments and returns a single value.
- doubleArray(int) -
Method in class flanagan.math.PsRandom
-
- DoubleArray - Interface in org.apache.commons.math.util
- Provides a standard interface for double arrays.
- 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.
- 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.
- 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.
- DoubleBuffer2DConsumer - Interface in cern.colt.buffer
- 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.
- DoubleBuffer3DConsumer - Interface in cern.colt.buffer
- 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.
- DoubleComparator - Interface in cern.colt.function
- A comparison function which imposes a total ordering on some
collection of elements.
- DoubleDoubleFunction - Interface in cern.colt.function
- 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.
- DoubleFactory1D - Class in cern.colt.matrix
- 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.
- DoubleFactory3D - Class in cern.colt.matrix
- Factory for convenient construction of 3-d matrices holding double cells.
- DoubleFunction - Interface in cern.colt.function
- Interface that represents a function object: a function that takes
a single argument and returns a single value.
- DoubleIntProcedure - Interface in cern.colt.function
- Interface that represents a procedure object: a procedure that takes
two arguments and does not return a value.
- 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.
- DoubleMatrix1D - Class in cern.colt.matrix
- 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.
- DoubleMatrix1DProcedure - Interface in cern.colt.matrix
- 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.
- DoubleMatrix2DComparator - Interface in cern.colt.matrix.doublealgo
- A comparison function which imposes a total ordering on some
collection of elements.
- DoubleMatrix2DProcedure - Interface in cern.colt.matrix
- 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.
- DoubleMatrix3DProcedure - Interface in cern.colt.matrix
- Interface that represents a condition or procedure object: takes
a single argument and returns a boolean value.
- 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.
- DoubleQuantileFinder - Interface in cern.jet.stat.quantile
- The interface shared by all quantile finders, no matter if they are exact or approximate.
- doubleTOint(double[]) -
Static method in class flanagan.math.Fmath
-
- doubleValue() -
Method in class org.apache.commons.math.fraction.Fraction
- Gets the fraction as a double.
- 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.
- draw(P1D) -
Method in class jhplot.HChart
- Draw data in form of P1D.
- draw(HLabel) -
Method in class jhplot.HPlot
- Draw a label.
- draw(HShape) -
Method in class jhplot.HPlot
- Draw a shape primitive to the Canvas.
- draw(H1D[]) -
Method in class jhplot.HPlot
- Draw array of histograms
- draw(H1D) -
Method in class jhplot.HPlot
- Plot 1D histogram.
- draw(F1D[]) -
Method in class jhplot.HPlot
- Draw array of P1D 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(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(H2D) -
Method in class jhplot.HPlot3D
- Draw H2D histogram
- draw(H2D, H2D) -
Method in class jhplot.HPlot3D
- Plot 2 H2D histograms on the same plot
- draw(F2D) -
Method in class jhplot.HPlot3D
- Draw F2D function
- 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
- drawAxis(int) -
Method in class jhplot.HPlot
- Returns whether an axis will be drawn or not.
- drawMirrorAxis(int) -
Method in class jhplot.HPlot
- Returns whether the mirror of an axis will be drawn or not.
- DrawOptions - Class in jhplot
- Main class which sets graphics attributes for H1D, F1D, P1D classes.
- 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)
- drawTicLabels(int) -
Method in class jhplot.HPlot
- Returns whether or not to draw tic labels
- drawTics(int) -
Method in class jhplot.HPlot
- Returns whether or not to draw tics (little lines on the axes).
- 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
-
- 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
-
- 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
-
- 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
-
- 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
-
- 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
-
- 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.
- durbinWatson(DoubleArrayList) -
Static method in class cern.jet.stat.Descriptive
- Durbin-Watson computation.
- 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)
.
EmpiricalDistribution
interface.object
is a
BigMatrixImpl
instance with the same dimensions as this
and all corresponding matrix entries are equal.
object
is a
RealMatrixImpl
instance with the same dimensions as this
and all corresponding matrix entries are equal.
object
is an
AbstractStorelessUnivariateStatistic
returning the same
values as this for getResult()
and getN()
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.
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 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.
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.
ExponentialDistribution
.FDistribution
.length
with values generated
using getNext() repeatedly.
float
elements; implemented with arrays.AbstractFloatList
to be viewed and treated as a JDK 1.2 AbstractList
.long <= value
.
Complex
object to produce a string.
Fraction
object to produce a string.
Fraction
object to produce a string.
Former
via method create();
Implementations of can use existing libraries such as corejava.PrintfFormat or corejava.Format or other.GammaDistribution
.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.
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.
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.
DoubleArray
.
ResizableArray
.
expansionMode
determines whether the internal storage
array grows additively (ADDITIVE_MODE) or multiplicatively
(MULTIPLICATIVE_MODE) when it is expanded.
Fraction
instance with the 2 parts
of a fraction Y/Z.
BigDecimal.ROUND_HALF_UP
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.
StatisticalSummary
describing this distribution.
StatisticalSummary
describing this distribution.
StatisticalSummaryValues
instance reporting current
statistics.
valuesFileURL
- 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 available values.
- getVariance() -
Method in class org.apache.commons.math.stat.descriptive.SummaryStatisticsImpl
- Returns the variance of the values that have been added.
- getVersion() -
Static method in class jhplot.JHPlot
- Get version information
- getWeight() -
Method in class cern.jet.random.sampling.WeightedRandomSampler
- Not yet commented.
- getWeightedResiduals() -
Method in class flanagan.analysis.Regression
-
- getWeights() -
Method in class flanagan.math.FourierTransform
-
- getWhoAm() -
Method in class jhplot.shapes.HShape
- Primitive type
- getWholeFormat() -
Method in class org.apache.commons.math.fraction.ProperFractionFormat
- Access the whole format.
- getWindowOption() -
Method in class flanagan.math.FourierTransform
-
- getWindowSize() -
Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
- Univariate has the ability to return only measures for the
last N elements added to the set of values.
- getWindowSize() -
Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatisticsImpl
- Access the window size.
- getX(int) -
Method in class jhplot.F1D
- get value in X
- getX() -
Method in class jhplot.HLabel
- Returns the X position of the text.
- getX(int) -
Method in class jhplot.P1D
- Return a specific X-value.
- getXBar() -
Method in class jhplot.regression.LRegression
- Get average x
- getXdata() -
Method in class flanagan.analysis.Regression
-
- 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 (systematical error).
- 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 (systematical error).
- getY(int) -
Method in class jhplot.F1D
- get value in Y
- getY() -
Method in class jhplot.HLabel
- Returns the Y position of the text.
- getY(int) -
Method in class jhplot.P1D
- Return a specific Y-value.
- getYBar() -
Method in class jhplot.regression.LRegression
- Get average Y
- getYcalc() -
Method in class flanagan.analysis.Regression
-
- getYdata() -
Method in class flanagan.analysis.Regression
-
- 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.
- getYscale() -
Method in class flanagan.analysis.Regression
-
- getYscaleOption() -
Method in class flanagan.analysis.Regression
-
- 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.
- GeV -
Static variable in class cern.clhep.Units
-
- GHFrame - Class in jhplot
- class to create main Farme with a 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 It uses 10% of the space
from the top for the global title
- 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 which keeps 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
-
- 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
-
- gram -
Static variable in class cern.clhep.Units
-
- gramToOunce(double) -
Static method in class flanagan.math.Fmath
-
- graph(Graphics) -
Method in class flanagan.math.FourierTransform
-
- 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.
- Grid - Class in hep.aida.ref.function
-
- Grid(IModelFunction) -
Constructor for class hep.aida.ref.function.Grid
-
- 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
-
- 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
-
- gumbelMaxOnePar() -
Method in class flanagan.analysis.Regression
-
- gumbelMaxOneParPlot() -
Method in class flanagan.analysis.Regression
-
- 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
-
- gumbelMaxRand(double, double, int) -
Static method in class flanagan.analysis.Stat
-
- gumbelMaxRand(double, double, int, long) -
Static method in class flanagan.analysis.Stat
-
- gumbelMaxStandard() -
Method in class flanagan.analysis.Regression
-
- gumbelMaxStandardPlot() -
Method in class flanagan.analysis.Regression
-
- gumbelMaxStandDev(double) -
Static method in class flanagan.analysis.Stat
-
- 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
-
- 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
-
- gumbelMinOnePar() -
Method in class flanagan.analysis.Regression
-
- gumbelMinOneParPlot() -
Method in class flanagan.analysis.Regression
-
- 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
-
- 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
-
- gumbelMinStandard() -
Method in class flanagan.analysis.Regression
-
- gumbelMinStandardPlot() -
Method in class flanagan.analysis.Regression
-
- gumbelMinStandDev(double) -
Static method in class flanagan.analysis.Stat
-
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.
HypergeometricDistribution
.AbstractStorelessUnivariateStatistic.increment(double)
in a loop over
the input array.
AbstractStorelessUnivariateStatistic.increment(double)
in a loop over
the specified portion of the input array.
int
elements; implemented with arrays.AbstractIntList
to be viewed and treated as a JDK 1.2 AbstractList
.p
.
p
.
p
.
p
.
p
.
p
.
p
.
p
.
p
.
p
.
p
.
Double.POSITIVE_INFINITY
or
Double.NEGATIVE_INFINITY
) and neither part
is NaN
.
java.util.Random
to implement
RandomGenerator
.long
elements; implemented with arrays.AbstractLongList
to be viewed and treated as a JDK 1.2 AbstractList
.LUDecomposition
, avoiding unnecessary memory allocation and copying.MathException
with no
detail message.
MathException
with specified
detail message.
MathException
with specified
nested Throwable
root cause.
MathException
with specified
detail message and nested Throwable
root cause.
Math
.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 array is empty.
Double.NaN
if the designated subarray
is empty.
m
.
m
.
UnivariateRealSolver
for the given function.
UnivariateRealSolver
for the given function.
UnivariateRealSolver
for the given function.
UnivariateRealSolver
for the given function.
UnivariateRealSolver
for the given function.
UnivariateRealSolver
for the given function.
DistributionFactory
DescriptiveStatistics
DescriptiveStatistics
SummaryStatistics
SummaryStatistics
TestFactory
UnivariateRealSolver
for the given function.
UnivariateRealSolver
for the given function.
UnivariateRealSolver
for the given function.
UnivariateRealSolver
for the given function.
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.
(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.
mean
.
(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.
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
.
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.
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.
k
whose entries
are selected randomly, without repetition, from the integers
0 through n-1
(inclusive).
>= 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.
lower
,upper
) (i.e., endpoints excluded).
NormalDistribution
.Object
elements; implemented with arrays.ObjectArrayList
to be viewed and treated as a JDK 1.2 AbstractList
.v
.
v
.
v
.
v
.
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
.
Complex
object.
Complex
object.
Fraction
object.
Fraction
object.
Fraction
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.
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.
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[])
.
PoissonDistribution
.y
raised to the power of x
.
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
.
m
.
v
.
m
.
v
.
m
.
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
.
(0.0,1.0)
(excluding 0.0 and 1.0).
java.util.Random
wrapping a
RandomGenerator
.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
.(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).
v
as the
data for the unique column of the v.length x 1
matrix
created.
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) 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.
valuesFileURL
.
DoubleArray
implementation that automatically
handles expanding and contracting its internal storage array as elements
are added and removed.d
d
expansionMode
.
long
seed.
long
seed.
long
seed.
row, column
using data in
the input subMatrix
array.
row, column
using data in
the input subMatrix
array.
valuesFileURL
using a string URL representation
valuesFileURL
short
elements; implemented with arrays.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
.
long
elements; implemented with arrays; not efficient; just to demonstrate which methods you must override to implement a fully functional list.SmpBlas.allocateBlas(int, cern.colt.matrix.linalg.Blas)
.
min
and max
.
startValue
.
b
.
b
.
b
.
b
.
b
.
b
.
b
.
b
.
b
.
z
2 for the given complex
argument.
isBiasCorrected
property.
isBiasCorrected
property and the supplied external moment.
FJTaskRunnerGroup.stats()
.
UnivariateStatistic
with
StorelessUnivariateStatistic.increment(double)
and StorelessUnivariateStatistic.incrementAll(double[])
methods for adding
values and updating internal state.m
.
m
.
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.
SummaryStatistics
implementation.Double.NaN
if the array is empty.
Double.NaN
if the designated subarray
is empty.
sampleStats
to mu
.
StatisticalSummary
instances, without the
assumption of equal subpopulation variances.
sampleStats
to mu
.
StatisticalSummary
instances, without the
assumption of equal subpopulation variances.
TDistribution
.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.
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.
Partitioning.triplePartition(int[],int[],int[],int,int,int[],int,int,int[])
except that it synchronously partitions double[] rather than int[] arrays.
Partitioning.triplePartition(int[],int[],int[],int,int,int)
except that it synchronously partitions double[] rather than int[] arrays.
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.
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.
mu
.
sample
is drawn equals mu
.
sampleStats
with the constant mu
.
stats
is
drawn equals mu
.
sample1
and sample2
are drawn from populations with the same mean,
with significance level alpha
.
sampleStats1
and sampleStats2
describe
datasets drawn from populations with the same mean, with significance
level alpha
.
mu
.
sample
is drawn equals mu
.
sampleStats
with the constant mu
.
stats
is
drawn equals mu
.
sample1
and sample2
are drawn from populations with the same mean,
with significance level alpha
.
sampleStats1
and sampleStats2
describe
datasets drawn from populations with the same mean, with significance
level alpha
.
TTest
interface.MersenneTwister
seeded with the given seed.
UnivariateRealSolver
instances.UnivariateRealSolverFactory
.UnivariateRealSolver
objects.isBiasCorrected
property.
isBiasCorrected
property
isBiasCorrected
property and the supplied external second moment.
Double.NaN
if the array is empty.
Double.NaN
if the designated subarray
is empty.
WeibullDistribution
.Property.ZERO
attached for tolerance.
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