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FastMath.abs
method wrapped as a ComposableFunction
.
BigFraction
.
FieldMatrix
methods regardless of the underlying storage.FractionFormat
and BigFractionFormat
.RandomGenerator
interface.RealVector
interface.StorelessUnivariateStatistic
interface.UnivariateStatistic
interface.FastMath.abs
method wrapped as a ComposableFunction
.
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
.
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
.
Frequency.addValue(Comparable)
instead
SummaryStatistics
from several data sets or
data set partitions.double[]
arrays.
double[]
arrays.
double[]
arrays.
double[]
arrays.
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
.
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.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
.BisectionSolver.solve(UnivariateRealFunction, double, double)
or
UnivariateRealSolver.solve(UnivariateRealFunction, double, double, double)
method.
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.
CauchyDistribution
.FastMath.cbrt
method wrapped as a ComposableFunction
.
FastMath.ceil
method wrapped as a ComposableFunction
.
checkOrder
method). To be removed in 3.0.
observed
and expected
frequency counts.
counts
array, viewed as a two-way table.
observed
and expected
frequency counts.
observed1
and observed2
.
ChiSquaredDistribution
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.AbstractRandomGenerator.nextGaussian()
.
valuesFileURL
after use in REPLAY_MODE.
Clusterable
points.data
sorted by comparator
.
Complex
utilities functions.UnivariateRealFunction
that can be composed with other functions.valuesFileURL
, using the default number of bins.
valuesFileURL
and binCount
bins.
NonLinearConjugateGradientOptimizer
.ConvergenceException.ConvergenceException(Localizable, Object...)
ConvergenceException.ConvergenceException(Throwable, Localizable, Object...)
IterativeAlgorithm
. The concept of "accuracy" is
currently is also contained in SimpleRealPointChecker
and similar classes.RandomVectorGenerator
that generates vectors with with
correlated components.FastMath.cos
method wrapped as a ComposableFunction
.
FastMath.cosh
method wrapped as a ComposableFunction
.
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
.
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.
x
).
x
).
x
).
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.
FieldMatrixChangingVisitor
interface.FieldMatrixPreservingVisitor
interface.RealMatrixChangingVisitor
interface.RealMatrixPreservingVisitor
interface.RealMatrix
field in a class.
RealVector
field in a class.
Dfp
which hides the radix-10000 artifacts of the superclass.Dfp
.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.org.apache.commons.math.exception
.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.
- 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.
- DiscreteRandomVariable - Interface in jhplot.math.num.random
- A random variable generator for a discrete distribution.
- disposeMe() -
Method in class jhplot.GHMargin
- Dispose this canvas
- 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
- Distribution - Interface in jhplot.math.num.pdf
- Base statistical distribution.
- Distribution - Interface in org.apache.commons.math.distribution
- Base interface for probability distributions.
- distroy() -
Method in class jhplot.HPlot
- Remove the canvas frame
- distroy() -
Method in class jhplot.HPlot2D
- Remove the canvas frame
- 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
-
- 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.
- 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.
- 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.
- 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.
- 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.
- 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
- 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
- drawData(VectorGraphics) -
Method in class jhplot.jadraw.JaAxes
- Draw data points
- 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.
- 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.
- drawStatBox(H1D, double, double, String) -
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.
- 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.
EmpiricalDistribution
interface.file
.
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)
.
Clusterable
for points with integer coordinates.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.FastMath.exp
method wrapped as a ComposableFunction
.
FastMath.expm1
method wrapped as a ComposableFunction
.
ExponentialDistribution
.StrictMath
.FDistribution
.length
with values generated
using getNext() repeatedly.
FirstMoment
identical
to the original
FastMath.floor
method wrapped as a ComposableFunction
.
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.
Format.format(Object)
on a default instance of
ComplexFormat.
Format.format(Object)
on a default instance of
RealVectorFormat.
Format.format(Object)
on a default instance of
Vector3DFormat.
FourthMoment
identical
to the original
FieldMatrix
/Fraction
matrix to a RealMatrix
.
GammaDistribution
.GaussianFunction
.GaussianFunction
).a
, b
, c
, and d
)
of a ParametricGaussianFunction
based on the specified observed
points.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.
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.
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
BigInteger
.
new LUDecompositionImpl(m)
.getDeterminant()
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.
BracketFinder.getLo()
.
BracketFinder.getMid()
.
StoppingCondition
in the last run.
MultivariateSummaryStatistics.addValue(double[])
MultivariateSummaryStatistics.addValue(double[])
data[p[0]],..,data[p[data.length-1]]
data.get(p[0]),..,data.get(p[data.length-1])
MultivariateSummaryStatistics.addValue(double[])
MultivariateSummaryStatistics.addValue(double[])
MultivariateSummaryStatistics.addValue(double[])
MultivariateSummaryStatistics.addValue(double[])
MultivariateSummaryStatistics.addValue(double[])
MultivariateSummaryStatistics.addValue(double[])
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.
OpenMapRealVector.getSparsity()
MultivariateSummaryStatistics.addValue(double[])
MultivariateSummaryStatistics.addValue(double[])
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
- 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.
- getVarianceDirection() -
Method in class org.apache.commons.math.stat.descriptive.moment.SemiVariance
- Returns the varianceDirection property.
- 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)
- 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 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.
- 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
-
- 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.
- 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.
- getXBar() -
Method in class jhplot.stat.LinReg
- Get average x
- getXBar() -
Method in class jhplot.stat.LinRegWeighted
- Get average x
- 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.
- 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.
- 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.
- 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.
- getYBar() -
Method in class jhplot.stat.LinReg
- Get average Y
- getYBar() -
Method in class jhplot.stat.LinRegWeighted
- Get average Y
- 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.
- 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.
- 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.
- 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
- 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
-
- GoalType - Enum in org.apache.commons.math.optimization
- Goal type for an optimization problem.
- 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.
- 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.
f (t) = a cos (ω t + φ)
.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.
HypergeometricDistribution
.x
and y
- sqrt(x2 +y2){0, 1, ..., n}
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
.
UnivariateRealIntegrator.integrate(UnivariateRealFunction, double, double)
since 2.0
IntegratorException.IntegratorException(Localizable, Object...)
SplineInterpolator
on the resulting fit.
InvalidMatrixException.InvalidMatrixException(Localizable, Object...)
new LUDecompositionImpl(m)
.getSolver()
.getInverse()
p
.
p
.
p
.
p
.
p
.
p
.
p
.
p
.
p
.
p
.
p
.
p
.
p
.
ComposableFunction
.
Double.POSITIVE_INFINITY
or
Double.NEGATIVE_INFINITY
) and neither part
is NaN
.
NaN
.
NaN
.
NaN
.
NaN
.
new LUDecompositionImpl(m)
.getSolver()
.isNonSingular()
java.util.Random
to implement
RandomGenerator
.Kurtosis
identical
to the original
LaguerreSolver.solve(UnivariateRealFunction, double, double)
or
UnivariateRealSolver.solve(UnivariateRealFunction, double, double, double)
method.
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.List
.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
.
LUDecomposition
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.
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
.MatrixIndexException.MatrixIndexException(Localizable, Object...)
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.
MullerSolver.solve(UnivariateRealFunction, double, double)
or
UnivariateRealSolver.solve(UnivariateRealFunction, double, double, double)
method.
BinaryFunction
.
BigInteger
, returning the result in reduced form.
m
.
m
.
m
.
m
.
m
.
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.ComposableFunction
.
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
.
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.
mean
.
F Distribution
.
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.
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).
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
.
NormalDistribution
.NotARotationMatrixException.NotARotationMatrixException(Localizable, Object...)
null
argument must throw
this exception.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
.
Complex
object.
Complex
object.
BigFraction
object.
BigFraction
object.
Fraction
object.
Fraction
object.
BigFraction
object.
Fraction
object.
Vector3D
object.
Vector3D
object.
RealVector
object.
RealVector
object.
PascalDistribution
.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.
PoissonDistribution
.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
).
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
.
Product
identical
to the original
Double.NaN
if the array is empty.
Double.NaN
if the designated subarray
is empty.
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
.RandomKey
s.Random
object.Random
delegate.
Random
delegate initialized with the given seed.
Random
delegate.
data
using the natural ordering on Doubles, with
NaN values handled according to nanStrategy
and ties
resolved using tiesStrategy.
optimization
algorithm
has converged.Array2DRowRealMatrix
v
as the
data for the unique column of the v.length x 1
matrix
created.
BigFraction
to its lowest terms.
LinearConstraint
.data
.
valuesFileURL
.
DoubleArray
implementation that automatically
handles expanding and contracting its internal storage array as elements
are added and removed.{n-1, ....
- reverse() -
Method in class jhplot.P0D
- Reverse the order of elements
- reverse() -
Method in class jhplot.P0I
- Reverse the order of elements
- 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
- 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 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(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 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(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 class jhplot.P1D
- Returns RMS for X-values.
- 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 class jhplot.P1D
- Returns RMS for Y-values.
- 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.
- 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.
- RootHistogramBrowser - Class in jhplot.root
- A simple application for browsing histograms in Root Files
- RootHistogramBrowser() -
Constructor for class jhplot.root.RootHistogramBrowser
- Histogram browser
- 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 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
-
- 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
-
- 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
- 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
d
FastMath.scalb(double, int)
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
.
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.
expansionMode
.
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.
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.
valuesFileURL
using a string URL representation
valuesFileURL
x
.
x
.
x
.
x
.
x
.
x
.
FastMath.signum
method wrapped as a ComposableFunction
.
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.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.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
FieldVector
interface with a OpenIntToFieldHashMap
backing store.RealMatrix
implementations that require sparse backing storageFastMath.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.
FixedStepHandler
into a StepHandler
.UnivariateStatistic
with
StorelessUnivariateStatistic.increment(double)
and StorelessUnivariateStatistic.incrementAll(double[])
methods for adding
values and updating internal state.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.
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.
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.sampleStats
to mu
.
StatisticalSummary
instances, without the
assumption of equal subpopulation variances.
sampleStats
to mu
.
StatisticalSummary
instances, without the
assumption of equal subpopulation variances.
FastMath.tan
method wrapped as a ComposableFunction
.
FastMath.tanh
method wrapped as a ComposableFunction
.
TDistribution
.ThirdMoment
identical
to the original
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.
TrapezoidIntegrator.integrate(UnivariateRealFunction, double, double)
method.
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.
- Trigonometric - Class in jhplot.math.num.special
- Utility class that provides methods related to the trigonometric functions.
- 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.
- 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
- 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 jhplot.math.ValueErr
- Create a two dimensional array of ValueErr objects of dimensions n and m with zeros
- 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
- typeForClass(Class) - Static method in class hep.aida.ref.ManagedObject
FastMath.ulp
method wrapped as a ComposableFunction
.
RandomVectorGenerator
that generates vectors with uncorrelated
components.MersenneTwister
),
in order to generate the individual components.
UnivariateRealSolver
instances.UnivariateRealSolverFactory
.UnivariateRealSolver
objects.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.
optimization algorithm
has converged.WeibullDistribution
.curve fitting
.ZipfDistribution
.
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