| Package | Description |
|---|---|
| org.apache.commons.math3.analysis.differentiation |
This package holds the main interfaces and basic building block classes
dealing with differentiation.
|
| org.apache.commons.math3.analysis.integration |
Numerical integration (quadrature) algorithms for univariate real functions.
|
| org.apache.commons.math3.analysis.interpolation |
Univariate real functions interpolation algorithms.
|
| org.apache.commons.math3.analysis.solvers |
Root finding algorithms, for univariate real functions.
|
| org.apache.commons.math3.complex |
Complex number type and implementations of complex transcendental
functions.
|
| org.apache.commons.math3.exception |
Specialized exceptions for algorithms errors.
|
| org.apache.commons.math3.fraction |
Fraction number type and fraction number formatting.
|
| org.apache.commons.math3.genetics |
This package provides Genetic Algorithms components and implementations.
|
| org.apache.commons.math3.geometry.euclidean.threed |
This package provides basic 3D geometry components.
|
| org.apache.commons.math3.geometry.euclidean.twod |
This package provides basic 2D geometry components.
|
| org.apache.commons.math3.geometry.euclidean.twod.hull |
This package provides algorithms to generate the convex hull
for a set of points in an two-dimensional euclidean space.
|
| org.apache.commons.math3.geometry.spherical.oned |
This package provides basic geometry components on the 1-sphere.
|
| org.apache.commons.math3.linear |
Linear algebra support.
|
| org.apache.commons.math3.ml.clustering |
Clustering algorithms.
|
| org.apache.commons.math3.ode |
This package provides classes to solve Ordinary Differential Equations problems.
|
| org.apache.commons.math3.random |
Random number and random data generators.
|
| org.apache.commons.math3.special |
Implementations of special functions such as Beta and Gamma.
|
| org.apache.commons.math3.stat |
Data storage, manipulation and summary routines.
|
| org.apache.commons.math3.stat.clustering |
All classes and sub-packages of this package are deprecated.
|
| org.apache.commons.math3.stat.correlation |
Correlations/Covariance computations.
|
| org.apache.commons.math3.stat.descriptive |
Generic univariate summary statistic objects.
|
| org.apache.commons.math3.stat.descriptive.moment |
Summary statistics based on moments.
|
| org.apache.commons.math3.stat.descriptive.rank |
Summary statistics based on ranks.
|
| org.apache.commons.math3.stat.descriptive.summary |
Other summary statistics.
|
| org.apache.commons.math3.stat.inference |
Classes providing hypothesis testing.
|
| org.apache.commons.math3.stat.regression |
Statistical routines involving multivariate data.
|
| org.apache.commons.math3.transform |
Implementations of transform methods, including Fast Fourier transforms.
|
| org.apache.commons.math3.util |
Convenience routines and common data structures used throughout the commons-math library.
|
| Modifier and Type | Method and Description |
|---|---|
DerivativeStructure[][] |
UnivariateDifferentiableMatrixFunction.value(DerivativeStructure x)
Compute the value for the function.
|
DerivativeStructure[] |
UnivariateDifferentiableVectorFunction.value(DerivativeStructure x)
Compute the value for the function.
|
DerivativeStructure[] |
MultivariateDifferentiableVectorFunction.value(DerivativeStructure[] point)
Compute the value for the function at the given point.
|
DerivativeStructure |
MultivariateDifferentiableFunction.value(DerivativeStructure[] point)
Compute the value for the function at the given point.
|
| Modifier and Type | Method and Description |
|---|---|
protected double |
IterativeLegendreGaussIntegrator.doIntegrate()
Method for implementing actual integration algorithms in derived
classes.
|
protected double |
TrapezoidIntegrator.doIntegrate()
Method for implementing actual integration algorithms in derived
classes.
|
protected double |
LegendreGaussIntegrator.doIntegrate()
Deprecated.
Method for implementing actual integration algorithms in derived
classes.
|
protected double |
MidPointIntegrator.doIntegrate()
Method for implementing actual integration algorithms in derived
classes.
|
double |
UnivariateIntegrator.integrate(int maxEval,
UnivariateFunction f,
double min,
double max)
Integrate the function in the given interval.
|
double |
BaseAbstractUnivariateIntegrator.integrate(int maxEval,
UnivariateFunction f,
double lower,
double upper)
Integrate the function in the given interval.
|
protected void |
BaseAbstractUnivariateIntegrator.setup(int maxEval,
UnivariateFunction f,
double lower,
double upper)
Prepare for computation.
|
| Constructor and Description |
|---|
LegendreGaussIntegrator(int n,
double relativeAccuracy,
double absoluteAccuracy)
Deprecated.
Build a Legendre-Gauss integrator with given accuracies.
|
LegendreGaussIntegrator(int n,
double relativeAccuracy,
double absoluteAccuracy,
int minimalIterationCount,
int maximalIterationCount)
Deprecated.
Build a Legendre-Gauss integrator with given accuracies and iterations counts.
|
LegendreGaussIntegrator(int n,
int minimalIterationCount,
int maximalIterationCount)
Deprecated.
Build a Legendre-Gauss integrator with given iteration counts.
|
| Modifier and Type | Method and Description |
|---|---|
MultivariateFunction |
MultivariateInterpolator.interpolate(double[][] xval,
double[] yval)
Computes an interpolating function for the data set.
|
UnivariateFunction |
UnivariateInterpolator.interpolate(double[] xval,
double[] yval)
Compute an interpolating function for the dataset.
|
| Modifier and Type | Method and Description |
|---|---|
double |
BaseUnivariateSolver.solve(int maxEval,
FUNC f,
double min,
double max)
Solve for a zero root in the given interval.
|
double |
BaseUnivariateSolver.solve(int maxEval,
FUNC f,
double min,
double max,
double startValue)
Solve for a zero in the given interval, start at
startValue. |
| Modifier and Type | Method and Description |
|---|---|
StringBuffer |
ComplexFormat.format(Object obj,
StringBuffer toAppendTo,
FieldPosition pos)
Formats a object to produce a string.
|
double |
RootsOfUnity.getReal(int k)
Get the real part of the
k-th n-th root of unity. |
static Complex |
ComplexUtils.polar2Complex(double r,
double theta)
Creates a complex number from the given polar representation.
|
| Modifier and Type | Class and Description |
|---|---|
class |
DimensionMismatchException
Exception to be thrown when two dimensions differ.
|
class |
InsufficientDataException
Exception to be thrown when there is insufficient data to perform a computation.
|
class |
MathIllegalNumberException
Base class for exceptions raised by a wrong number.
|
class |
MultiDimensionMismatchException
Exception to be thrown when two sets of dimensions differ.
|
class |
NoBracketingException
Exception to be thrown when function values have the same sign at both
ends of an interval.
|
class |
NoDataException
Exception to be thrown when the required data is missing.
|
class |
NonMonotonicSequenceException
Exception to be thrown when the a sequence of values is not monotonically
increasing or decreasing.
|
class |
NotANumberException
Exception to be thrown when a number is not a number.
|
class |
NotFiniteNumberException
Exception to be thrown when a number is not finite.
|
class |
NotPositiveException
Exception to be thrown when the argument is negative.
|
class |
NotStrictlyPositiveException
Exception to be thrown when the argument is not greater than 0.
|
class |
NullArgumentException
All conditions checks that fail due to a
null argument must throw
this exception. |
class |
NumberIsTooLargeException
Exception to be thrown when a number is too large.
|
class |
NumberIsTooSmallException
Exception to be thrown when a number is too small.
|
class |
OutOfRangeException
Exception to be thrown when some argument is out of range.
|
class |
ZeroException
Exception to be thrown when zero is provided where it is not allowed.
|
| Modifier and Type | Method and Description |
|---|---|
StringBuffer |
FractionFormat.format(Object obj,
StringBuffer toAppendTo,
FieldPosition pos)
Formats an object and appends the result to a StringBuffer.
|
| Constructor and Description |
|---|
BigFraction(double value)
Create a fraction given the double value.
|
| Modifier and Type | Class and Description |
|---|---|
class |
InvalidRepresentationException
Exception indicating that the representation of a chromosome is not valid.
|
| Modifier and Type | Method and Description |
|---|---|
ChromosomePair |
OnePointCrossover.crossover(Chromosome first,
Chromosome second)
Performs one point crossover.
|
ChromosomePair |
CrossoverPolicy.crossover(Chromosome first,
Chromosome second)
Perform a crossover operation on the given chromosomes.
|
ChromosomePair |
CycleCrossover.crossover(Chromosome first,
Chromosome second)
Perform a crossover operation on the given chromosomes.
|
ChromosomePair |
NPointCrossover.crossover(Chromosome first,
Chromosome second)
Performs a N-point crossover.
|
ChromosomePair |
OrderedCrossover.crossover(Chromosome first,
Chromosome second)
Perform a crossover operation on the given chromosomes.
|
ChromosomePair |
UniformCrossover.crossover(Chromosome first,
Chromosome second)
Perform a crossover operation on the given chromosomes.
|
static <S> List<Double> |
RandomKey.inducedPermutation(List<S> originalData,
List<S> permutedData)
Generates a representation of a permutation corresponding to a
permutation which yields
permutedData when applied to
originalData. |
Chromosome |
BinaryMutation.mutate(Chromosome original)
Mutate the given chromosome.
|
Chromosome |
MutationPolicy.mutate(Chromosome original)
Mutate the given chromosome.
|
Chromosome |
RandomKeyMutation.mutate(Chromosome original)
Mutate the given chromosome.
|
ChromosomePair |
SelectionPolicy.select(Population population)
Select two chromosomes from the population.
|
ChromosomePair |
TournamentSelection.select(Population population)
Select two chromosomes from the population.
|
| Modifier and Type | Class and Description |
|---|---|
class |
NotARotationMatrixException
This class represents exceptions thrown while building rotations
from matrices.
|
| Modifier and Type | Method and Description |
|---|---|
void |
Line.reset(Vector3D p1,
Vector3D p2)
Reset the instance as if built from two points.
|
| Constructor and Description |
|---|
FieldRotation(FieldVector3D<T> axis,
T angle)
Deprecated.
as of 3.6, replaced with
FieldRotation.FieldRotation(FieldVector3D, RealFieldElement, RotationConvention) |
FieldRotation(FieldVector3D<T> axis,
T angle,
RotationConvention convention)
Build a rotation from an axis and an angle.
|
Line(Vector3D p1,
Vector3D p2)
Deprecated.
as of 3.3, replaced with
Line.Line(Vector3D, Vector3D, double) |
Line(Vector3D p1,
Vector3D p2,
double tolerance)
Build a line from two points.
|
Rotation(Vector3D axis,
double angle)
Deprecated.
as of 3.6, replaced with
Rotation.Rotation(Vector3D, double, RotationConvention) |
Rotation(Vector3D axis,
double angle,
RotationConvention convention)
Build a rotation from an axis and an angle.
|
SubLine(Segment segment)
Create a sub-line from a segment.
|
SubLine(Vector3D start,
Vector3D end)
Deprecated.
as of 3.3, replaced with
SubLine.SubLine(Vector3D, Vector3D, double) |
SubLine(Vector3D start,
Vector3D end,
double tolerance)
Create a sub-line from two endpoints.
|
| Modifier and Type | Method and Description |
|---|---|
static Transform<Euclidean2D,Euclidean1D> |
Line.getTransform(AffineTransform transform)
Deprecated.
as of 3.6, replaced with
Line.getTransform(double, double, double, double, double, double) |
static Transform<Euclidean2D,Euclidean1D> |
Line.getTransform(double cXX,
double cYX,
double cXY,
double cYY,
double cX1,
double cY1)
Get a
Transform embedding an affine transform. |
| Constructor and Description |
|---|
ConvexHull2D(Vector2D[] vertices,
double tolerance)
Simple constructor.
|
| Modifier and Type | Class and Description |
|---|---|
static class |
ArcsSet.InconsistentStateAt2PiWrapping
Specialized exception for inconsistent BSP tree state inconsistency.
|
| Modifier and Type | Class and Description |
|---|---|
class |
IllConditionedOperatorException
An exception to be thrown when the condition number of a
RealLinearOperator is too high. |
class |
MatrixDimensionMismatchException
Exception to be thrown when either the number of rows or the number of
columns of a matrix do not match the expected values.
|
class |
NonPositiveDefiniteMatrixException
Exception to be thrown when a positive definite matrix is expected.
|
class |
NonPositiveDefiniteOperatorException
Exception to be thrown when a symmetric, definite positive
RealLinearOperator is expected. |
class |
NonSelfAdjointOperatorException
Exception to be thrown when a self-adjoint
RealLinearOperator
is expected. |
class |
NonSquareMatrixException
Exception to be thrown when a square matrix is expected.
|
class |
NonSquareOperatorException
Exception to be thrown when a square linear operator is expected.
|
class |
NonSymmetricMatrixException
Exception to be thrown when a symmetric matrix is expected.
|
class |
SingularMatrixException
Exception to be thrown when a non-singular matrix is expected.
|
class |
SingularOperatorException
Exception to be thrown when trying to invert a singular operator.
|
| Modifier and Type | Method and Description |
|---|---|
List<CentroidCluster<T>> |
KMeansPlusPlusClusterer.cluster(Collection<T> points)
Runs the K-means++ clustering algorithm.
|
List<CentroidCluster<T>> |
FuzzyKMeansClusterer.cluster(Collection<T> dataPoints)
Performs Fuzzy K-Means cluster analysis.
|
abstract List<? extends Cluster<T>> |
Clusterer.cluster(Collection<T> points)
Perform a cluster analysis on the given set of
Clusterable instances. |
List<CentroidCluster<T>> |
MultiKMeansPlusPlusClusterer.cluster(Collection<T> points)
Runs the K-means++ clustering algorithm.
|
| Modifier and Type | Class and Description |
|---|---|
static class |
JacobianMatrices.MismatchedEquations
Special exception for equations mismatch.
|
class |
UnknownParameterException
Exception to be thrown when a parameter is unknown.
|
| Modifier and Type | Method and Description |
|---|---|
void |
ContinuousOutputFieldModel.append(ContinuousOutputFieldModel<T> model)
Append another model at the end of the instance.
|
void |
ContinuousOutputModel.append(ContinuousOutputModel model)
Append another model at the end of the instance.
|
T[] |
FieldEquationsMapper.extractEquationData(int index,
T[] complete)
Extract equation data from a complete state or derivative array.
|
void |
SecondOrderIntegrator.integrate(SecondOrderDifferentialEquations equations,
double t0,
double[] y0,
double[] yDot0,
double t,
double[] y,
double[] yDot)
Integrate the differential equations up to the given time
|
| Modifier and Type | Method and Description |
|---|---|
void |
ValueServer.fill(double[] values)
Fills the input array with values generated using getNext() repeatedly.
|
double[] |
ValueServer.fill(int length)
Returns an array of length
length with values generated
using getNext() repeatedly. |
double |
ValueServer.getNext()
Returns the next generated value, generated according
to the mode value (see MODE constants).
|
int |
RandomDataImpl.nextInversionDeviate(IntegerDistribution distribution)
Deprecated.
use the distribution's sample() method
|
double |
RandomDataImpl.nextInversionDeviate(RealDistribution distribution)
Deprecated.
use the distribution's sample() method
|
| Modifier and Type | Method and Description |
|---|---|
double |
BesselJ.value(double x)
Returns the value of the constructed Bessel function of the first kind,
for the passed argument.
|
static double |
BesselJ.value(double order,
double x)
Returns the first Bessel function, \(J_{order}(x)\).
|
| Modifier and Type | Method and Description |
|---|---|
void |
Frequency.addValue(char v)
Adds 1 to the frequency count for v.
|
void |
Frequency.addValue(Comparable<?> v)
Adds 1 to the frequency count for v.
|
void |
Frequency.addValue(int v)
Adds 1 to the frequency count for v.
|
void |
Frequency.addValue(long v)
Adds 1 to the frequency count for v.
|
static double |
StatUtils.geometricMean(double[] values)
Returns the geometric mean of the entries in the input array, or
Double.NaN if the array is empty. |
static double |
StatUtils.geometricMean(double[] values,
int begin,
int length)
Returns the geometric mean of the entries in the specified portion of
the input array, or
Double.NaN if the designated subarray
is empty. |
void |
Frequency.incrementValue(char v,
long increment)
Increments the frequency count for v.
|
void |
Frequency.incrementValue(Comparable<?> v,
long increment)
Increments the frequency count for v.
|
void |
Frequency.incrementValue(int v,
long increment)
Increments the frequency count for v.
|
void |
Frequency.incrementValue(long v,
long increment)
Increments the frequency count for v.
|
static double |
StatUtils.max(double[] values)
Returns the maximum of the entries in the input array, or
Double.NaN if the array is empty. |
static double |
StatUtils.max(double[] values,
int begin,
int length)
Returns the maximum of the entries in the specified portion of
the input array, or
Double.NaN if the designated subarray
is empty. |
static double |
StatUtils.mean(double[] values)
Returns the arithmetic mean of the entries in the input array, or
Double.NaN if the array is empty. |
static double |
StatUtils.mean(double[] values,
int begin,
int length)
Returns the arithmetic mean of the entries in the specified portion of
the input array, or
Double.NaN if the designated subarray
is empty. |
static double |
StatUtils.min(double[] values)
Returns the minimum of the entries in the input array, or
Double.NaN if the array is empty. |
static double |
StatUtils.min(double[] values,
int begin,
int length)
Returns the minimum of the entries in the specified portion of
the input array, or
Double.NaN if the designated subarray
is empty. |
static double[] |
StatUtils.mode(double[] sample)
Returns the sample mode(s).
|
static double |
StatUtils.percentile(double[] values,
double p)
Returns an estimate of the
pth percentile of the values
in the values array. |
static double |
StatUtils.percentile(double[] values,
int begin,
int length,
double p)
Returns an estimate of the
pth percentile of the values
in the values array, starting with the element in (0-based)
position begin in the array and including length
values. |
static double |
StatUtils.populationVariance(double[] values)
Returns the
population variance of the entries in the input array, or
Double.NaN if the array is empty. |
static double |
StatUtils.populationVariance(double[] values,
double mean)
Returns the
population variance of the entries in the input array, using the
precomputed mean value.
|
static double |
StatUtils.populationVariance(double[] values,
double mean,
int begin,
int length)
Returns the
population variance of the entries in the specified portion of
the input array, using the precomputed mean value.
|
static double |
StatUtils.populationVariance(double[] values,
int begin,
int length)
Returns the
population variance of the entries in the specified portion of
the input array, or
Double.NaN if the designated subarray
is empty. |
static double |
StatUtils.product(double[] values)
Returns the product of the entries in the input array, or
Double.NaN if the array is empty. |
static double |
StatUtils.product(double[] values,
int begin,
int length)
Returns the product of the entries in the specified portion of
the input array, or
Double.NaN if the designated subarray
is empty. |
static double |
StatUtils.sum(double[] values)
Returns the sum of the values in the input array, or
Double.NaN if the array is empty. |
static double |
StatUtils.sum(double[] values,
int begin,
int length)
Returns the sum of the entries in the specified portion of
the input array, or
Double.NaN if the designated subarray
is empty. |
static double |
StatUtils.sumLog(double[] values)
Returns the sum of the natural logs of the entries in the input array, or
Double.NaN if the array is empty. |
static double |
StatUtils.sumLog(double[] values,
int begin,
int length)
Returns the sum of the natural logs of the entries in the specified portion of
the input array, or
Double.NaN if the designated subarray
is empty. |
static double |
StatUtils.sumSq(double[] values)
Returns the sum of the squares of the entries in the input array, or
Double.NaN if the array is empty. |
static double |
StatUtils.sumSq(double[] values,
int begin,
int length)
Returns the sum of the squares of the entries in the specified portion of
the input array, or
Double.NaN if the designated subarray
is empty. |
static double |
StatUtils.variance(double[] values)
Returns the variance of the entries in the input array, or
Double.NaN if the array is empty. |
static double |
StatUtils.variance(double[] values,
double mean)
Returns the variance of the entries in the input array, using the
precomputed mean value.
|
static double |
StatUtils.variance(double[] values,
double mean,
int begin,
int length)
Returns the variance of the entries in the specified portion of
the input array, using the precomputed mean value.
|
static double |
StatUtils.variance(double[] values,
int begin,
int length)
Returns the variance of the entries in the specified portion of
the input array, or
Double.NaN if the designated subarray
is empty. |
| Modifier and Type | Method and Description |
|---|---|
List<Cluster<T>> |
KMeansPlusPlusClusterer.cluster(Collection<T> points,
int k,
int maxIterations)
Deprecated.
Runs the K-means++ clustering algorithm.
|
List<Cluster<T>> |
KMeansPlusPlusClusterer.cluster(Collection<T> points,
int k,
int numTrials,
int maxIterationsPerTrial)
Deprecated.
Runs the K-means++ clustering algorithm.
|
| Modifier and Type | Method and Description |
|---|---|
protected RealMatrix |
Covariance.computeCovarianceMatrix(double[][] data)
Create a covariance matrix from a rectangular array whose columns represent
covariates.
|
protected RealMatrix |
Covariance.computeCovarianceMatrix(double[][] data,
boolean biasCorrected)
Compute a covariance matrix from a rectangular array whose columns represent
covariates.
|
protected RealMatrix |
Covariance.computeCovarianceMatrix(RealMatrix matrix)
Create a covariance matrix from a matrix whose columns represent
covariates.
|
protected RealMatrix |
Covariance.computeCovarianceMatrix(RealMatrix matrix,
boolean biasCorrected)
Compute a covariance matrix from a matrix whose columns represent
covariates.
|
double |
Covariance.covariance(double[] xArray,
double[] yArray)
Computes the covariance between the two arrays, using the bias-corrected
formula.
|
double |
Covariance.covariance(double[] xArray,
double[] yArray,
boolean biasCorrected)
Computes the covariance between the two arrays.
|
| Constructor and Description |
|---|
Covariance(double[][] data)
Create a Covariance matrix from a rectangular array
whose columns represent covariates.
|
Covariance(double[][] data,
boolean biasCorrected)
Create a Covariance matrix from a rectangular array
whose columns represent covariates.
|
Covariance(RealMatrix matrix)
Create a covariance matrix from a matrix whose columns
represent covariates.
|
Covariance(RealMatrix matrix,
boolean biasCorrected)
Create a covariance matrix from a matrix whose columns
represent covariates.
|
| Modifier and Type | Method and Description |
|---|---|
double |
AbstractUnivariateStatistic.evaluate()
Returns the result of evaluating the statistic over the stored data.
|
double |
AbstractUnivariateStatistic.evaluate(double[] values)
Returns the result of evaluating the statistic over the input array.
|
double |
UnivariateStatistic.evaluate(double[] values)
Returns the result of evaluating the statistic over the input array.
|
double |
AbstractStorelessUnivariateStatistic.evaluate(double[] values)
This default implementation calls
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. |
double |
WeightedEvaluation.evaluate(double[] values,
double[] weights)
Returns the result of evaluating the statistic over the input array,
using the supplied weights.
|
double |
WeightedEvaluation.evaluate(double[] values,
double[] weights,
int begin,
int length)
Returns the result of evaluating the statistic over the specified entries
in the input array, using corresponding entries in the supplied weights array.
|
abstract double |
AbstractUnivariateStatistic.evaluate(double[] values,
int begin,
int length)
Returns the result of evaluating the statistic over the specified entries
in the input array.
|
double |
UnivariateStatistic.evaluate(double[] values,
int begin,
int length)
Returns the result of evaluating the statistic over the specified entries
in the input array.
|
double |
AbstractStorelessUnivariateStatistic.evaluate(double[] values,
int begin,
int length)
This default implementation calls
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 |
DescriptiveStatistics.getPercentile(double p)
Returns an estimate for the pth percentile of the stored values.
|
void |
AbstractStorelessUnivariateStatistic.incrementAll(double[] values)
This default implementation just calls
AbstractStorelessUnivariateStatistic.increment(double) in a loop over
the input array. |
void |
StorelessUnivariateStatistic.incrementAll(double[] values)
Updates the internal state of the statistic to reflect addition of
all values in the values array.
|
void |
AbstractStorelessUnivariateStatistic.incrementAll(double[] values,
int begin,
int length)
This default implementation just calls
AbstractStorelessUnivariateStatistic.increment(double) in a loop over
the specified portion of the input array. |
void |
StorelessUnivariateStatistic.incrementAll(double[] values,
int start,
int length)
Updates the internal state of the statistic to reflect addition of
the values in the designated portion of the values array.
|
void |
AbstractUnivariateStatistic.setData(double[] values,
int begin,
int length)
Set the data array.
|
void |
DescriptiveStatistics.setPercentileImpl(UnivariateStatistic percentileImpl)
Sets the implementation to be used by
DescriptiveStatistics.getPercentile(double). |
void |
DescriptiveStatistics.setWindowSize(int windowSize)
WindowSize controls the number of values that contribute to the
reported statistics.
|
void |
SynchronizedDescriptiveStatistics.setWindowSize(int windowSize)
WindowSize controls the number of values that contribute to the
reported statistics.
|
protected boolean |
AbstractUnivariateStatistic.test(double[] values,
double[] weights,
int begin,
int length)
This method is used by
evaluate(double[], double[], int, int) methods
to verify that the begin and length parameters designate a subarray of positive length
and the weights are all non-negative, non-NaN, finite, and not all zero. |
protected boolean |
AbstractUnivariateStatistic.test(double[] values,
double[] weights,
int begin,
int length,
boolean allowEmpty)
This method is used by
evaluate(double[], double[], int, int) methods
to verify that the begin and length parameters designate a subarray of positive length
and the weights are all non-negative, non-NaN, finite, and not all zero. |
protected boolean |
AbstractUnivariateStatistic.test(double[] values,
int begin,
int length)
This method is used by
evaluate(double[], int, int) methods
to verify that the input parameters designate a subarray of positive length. |
protected boolean |
AbstractUnivariateStatistic.test(double[] values,
int begin,
int length,
boolean allowEmpty)
This method is used by
evaluate(double[], int, int) methods
to verify that the input parameters designate a subarray of positive length. |
| Constructor and Description |
|---|
DescriptiveStatistics(int window)
Construct a DescriptiveStatistics instance with the specified window
|
SynchronizedDescriptiveStatistics(int window)
Construct an instance with finite window
|
| Modifier and Type | Method and Description |
|---|---|
double |
Variance.evaluate(double[] values)
Returns the variance of the entries in the input array, or
Double.NaN if the array is empty. |
double |
StandardDeviation.evaluate(double[] values)
Returns the Standard Deviation of the entries in the input array, or
Double.NaN if the array is empty. |
double |
SemiVariance.evaluate(double[] values,
double cutoff)
Returns the
SemiVariance of the designated values against the cutoff, using
instance properties variancDirection and biasCorrection. |
double |
Variance.evaluate(double[] values,
double mean)
Returns the variance of the entries in the input array, using the
precomputed mean value.
|
double |
StandardDeviation.evaluate(double[] values,
double mean)
Returns the Standard Deviation of the entries in the input array, using
the precomputed mean value.
|
double |
Mean.evaluate(double[] values,
double[] weights)
Returns the weighted arithmetic mean of the entries in the input array.
|
double |
Variance.evaluate(double[] values,
double[] weights)
Returns the weighted variance of the entries in the the input array.
|
double |
Variance.evaluate(double[] values,
double[] weights,
double mean)
Returns the weighted variance of the values in the input array, using
the precomputed weighted mean value.
|
double |
Variance.evaluate(double[] values,
double[] weights,
double mean,
int begin,
int length)
Returns the weighted variance of the entries in the specified portion of
the input array, using the precomputed weighted mean value.
|
double |
Mean.evaluate(double[] values,
double[] weights,
int begin,
int length)
Returns the weighted arithmetic mean of the entries in the specified portion of
the input array, or
Double.NaN if the designated subarray
is empty. |
double |
Variance.evaluate(double[] values,
double[] weights,
int begin,
int length)
Returns the weighted variance of the entries in the specified portion of
the input array, or
Double.NaN if the designated subarray
is empty. |
double |
Variance.evaluate(double[] values,
double mean,
int begin,
int length)
Returns the variance of the entries in the specified portion of
the input array, using the precomputed mean value.
|
double |
StandardDeviation.evaluate(double[] values,
double mean,
int begin,
int length)
Returns the Standard Deviation of the entries in the specified portion of
the input array, using the precomputed mean value.
|
double |
SemiVariance.evaluate(double[] values,
double cutoff,
SemiVariance.Direction direction)
Returns the
SemiVariance of the designated values against the cutoff in the
given direction, using the current value of the biasCorrection instance property. |
double |
SemiVariance.evaluate(double[] values,
double cutoff,
SemiVariance.Direction direction,
boolean corrected,
int start,
int length)
Returns the
SemiVariance of the designated values against the cutoff
in the given direction with the provided bias correction. |
double |
SemiVariance.evaluate(double[] values,
int start,
int length)
Returns the
SemiVariance of the designated values against the mean, using
instance properties varianceDirection and biasCorrection. |
double |
Mean.evaluate(double[] values,
int begin,
int length)
Returns the arithmetic mean of the entries in the specified portion of
the input array, or
Double.NaN if the designated subarray
is empty. |
double |
Kurtosis.evaluate(double[] values,
int begin,
int length)
Returns the kurtosis of the entries in the specified portion of the
input array.
|
double |
GeometricMean.evaluate(double[] values,
int begin,
int length)
Returns the geometric mean of the entries in the specified portion
of the input array.
|
double |
Variance.evaluate(double[] values,
int begin,
int length)
Returns the variance of the entries in the specified portion of
the input array, or
Double.NaN if the designated subarray
is empty. |
double |
Skewness.evaluate(double[] values,
int begin,
int length)
Returns the Skewness of the entries in the specifed portion of the
input array.
|
double |
StandardDeviation.evaluate(double[] values,
int begin,
int length)
Returns the Standard Deviation of the entries in the specified portion of
the input array, or
Double.NaN if the designated subarray
is empty. |
double |
SemiVariance.evaluate(double[] values,
SemiVariance.Direction direction)
This method calculates
SemiVariance for the entire array against the mean, using
the current value of the biasCorrection instance property. |
| Modifier and Type | Method and Description |
|---|---|
double |
Percentile.evaluate(double p)
Returns the result of evaluating the statistic over the stored data.
|
double |
Percentile.evaluate(double[] values,
double p)
Returns an estimate of the
pth percentile of the values
in the values array. |
double |
Max.evaluate(double[] values,
int begin,
int length)
Returns the maximum of the entries in the specified portion of
the input array, or
Double.NaN if the designated subarray
is empty. |
double |
Min.evaluate(double[] values,
int begin,
int length)
Returns the minimum of the entries in the specified portion of
the input array, or
Double.NaN if the designated subarray
is empty. |
double |
Percentile.evaluate(double[] values,
int start,
int length)
Returns an estimate of the
quantileth percentile of the
designated values in the values array. |
double |
Percentile.evaluate(double[] values,
int begin,
int length,
double p)
Returns an estimate of the
pth percentile of the values
in the values array, starting with the element in (0-based)
position begin in the array and including length
values. |
void |
Percentile.setData(double[] values,
int begin,
int length)
Set the data array.
|
void |
Percentile.setQuantile(double p)
Sets the value of the quantile field (determines what percentile is
computed when evaluate() is called with no quantile argument).
|
| Constructor and Description |
|---|
Percentile(double quantile)
Constructs a Percentile with the specific quantile value and the following
default method type:
Percentile.EstimationType.LEGACY
default NaN strategy: NaNStrategy.REMOVED
a Kth Selector : KthSelector
|
Percentile(double quantile,
Percentile.EstimationType estimationType,
NaNStrategy nanStrategy,
KthSelector kthSelector)
Constructs a Percentile with the specific quantile value,
Percentile.EstimationType, NaNStrategy and KthSelector. |
| Modifier and Type | Method and Description |
|---|---|
double |
Sum.evaluate(double[] values,
double[] weights)
The weighted sum of the entries in the the input array.
|
double |
Product.evaluate(double[] values,
double[] weights)
Returns the weighted product of the entries in the input array.
|
double |
Sum.evaluate(double[] values,
double[] weights,
int begin,
int length)
The weighted sum of the entries in the specified portion of
the input array, or 0 if the designated subarray
is empty.
|
double |
Product.evaluate(double[] values,
double[] weights,
int begin,
int length)
Returns the weighted product of the entries in the specified portion of
the input array, or
Double.NaN if the designated subarray
is empty. |
double |
SumOfLogs.evaluate(double[] values,
int begin,
int length)
Returns the sum of the natural logs of the entries in the specified portion of
the input array, or
Double.NaN if the designated subarray
is empty. |
double |
Sum.evaluate(double[] values,
int begin,
int length)
The sum of the entries in the specified portion of
the input array, or 0 if the designated subarray
is empty.
|
double |
Product.evaluate(double[] values,
int begin,
int length)
Returns the product of the entries in the specified portion of
the input array, or
Double.NaN if the designated subarray
is empty. |
double |
SumOfSquares.evaluate(double[] values,
int begin,
int length)
Returns the sum of the squares of the entries in the specified portion of
the input array, or
Double.NaN if the designated subarray
is empty. |
| Modifier and Type | Method and Description |
|---|---|
protected double |
TTest.tTest(double m,
double mu,
double v,
double n)
Computes p-value for 2-sided, 1-sample t-test.
|
| Modifier and Type | Class and Description |
|---|---|
class |
ModelSpecificationException
Exception thrown when a regression model is not correctly specified.
|
| Modifier and Type | Method and Description |
|---|---|
void |
OLSMultipleLinearRegression.newSampleData(double[] y,
double[][] x)
Loads model x and y sample data, overriding any previous sample.
|
RegressionResults |
SimpleRegression.regress(int[] variablesToInclude)
Performs a regression on data present in buffers including only regressors
indexed in variablesToInclude and outputs a RegressionResults object
|
RegressionResults |
UpdatingMultipleLinearRegression.regress(int[] variablesToInclude)
Performs a regression on data present in buffers including only regressors
indexed in variablesToInclude and outputs a RegressionResults object
|
protected void |
AbstractMultipleLinearRegression.validateSampleData(double[][] x,
double[] y)
Validates sample data.
|
| Modifier and Type | Method and Description |
|---|---|
static int |
TransformUtils.exactLog2(int n)
Returns the base-2 logarithm of the specified
int. |
protected double[] |
FastCosineTransformer.fct(double[] f)
Perform the FCT algorithm (including inverse).
|
protected double[] |
FastHadamardTransformer.fht(double[] x)
The FHT (Fast Hadamard Transformation) which uses only subtraction and
addition.
|
protected int[] |
FastHadamardTransformer.fht(int[] x)
Returns the forward transform of the specified integer data set.
|
protected double[] |
FastSineTransformer.fst(double[] f)
Perform the FST algorithm (including inverse).
|
double[] |
RealTransformer.transform(double[] f,
TransformType type)
Returns the (forward, inverse) transform of the specified real data set.
|
double[] |
FastCosineTransformer.transform(double[] f,
TransformType type)
Returns the (forward, inverse) transform of the specified real data set.
|
double[] |
RealTransformer.transform(UnivariateFunction f,
double min,
double max,
int n,
TransformType type)
Returns the (forward, inverse) transform of the specified real function,
sampled on the specified interval.
|
double[] |
FastCosineTransformer.transform(UnivariateFunction f,
double min,
double max,
int n,
TransformType type)
Returns the (forward, inverse) transform of the specified real function,
sampled on the specified interval.
|
| Modifier and Type | Method and Description |
|---|---|
protected void |
ResizableDoubleArray.checkContractExpand(float contraction,
float expansion)
Deprecated.
As of 3.1. Please use
ResizableDoubleArray.checkContractExpand(double,double) instead. |
void |
ResizableDoubleArray.discardFrontElements(int i)
Discards the
i initial elements of the array. |
void |
ResizableDoubleArray.discardMostRecentElements(int i)
Discards the
i last elements of the array. |
static double[] |
MathArrays.normalizeArray(double[] values,
double normalizedSum)
Normalizes an array to make it sum to a specified value.
|
int |
CentralPivotingStrategy.pivotIndex(double[] work,
int begin,
int end)
Find pivot index of the array so that partition and Kth
element selection can be made
|
int |
RandomPivotingStrategy.pivotIndex(double[] work,
int begin,
int end)
Find pivot index of the array so that partition and Kth
element selection can be made
|
int |
MedianOf3PivotingStrategy.pivotIndex(double[] work,
int begin,
int end)
Find pivot index of the array so that partition and Kth
element selection can be made
|
int |
PivotingStrategyInterface.pivotIndex(double[] work,
int begin,
int end)
Find pivot index of the array so that partition and Kth
element selection can be made
|
static float |
Precision.round(float x,
int scale,
int roundingMethod)
Rounds the given value to the specified number of decimal places.
|
void |
ResizableDoubleArray.setContractionCriteria(float contractionCriteria)
Deprecated.
As of 3.1 (to be removed in 4.0 as field will become "final").
|
void |
ResizableDoubleArray.setExpansionFactor(float expansionFactor)
Deprecated.
As of 3.1 (to be removed in 4.0 as field will become "final").
|
void |
ResizableDoubleArray.setExpansionMode(int expansionMode)
Deprecated.
As of 3.1. Please use
ResizableDoubleArray.setExpansionMode(ExpansionMode) instead. |
protected void |
ResizableDoubleArray.setInitialCapacity(int initialCapacity)
Deprecated.
As of 3.1, this is a no-op.
|
void |
ResizableDoubleArray.setNumElements(int i)
This function allows you to control the number of elements contained
in this array, and can be used to "throw out" the last n values in an
array.
|
double |
DefaultTransformer.transform(Object o) |
double |
NumberTransformer.transform(Object o)
Implementing this interface provides a facility to transform
from Object to Double.
|
double |
TransformerMap.transform(Object o)
Attempts to transform the Object against the map of
NumberTransformers.
|
static boolean |
MathArrays.verifyValues(double[] values,
double[] weights,
int begin,
int length)
This method is used
to verify that the begin and length parameters designate a subarray of positive length
and the weights are all non-negative, non-NaN, finite, and not all zero.
|
static boolean |
MathArrays.verifyValues(double[] values,
double[] weights,
int begin,
int length,
boolean allowEmpty)
This method is used
to verify that the begin and length parameters designate a subarray of positive length
and the weights are all non-negative, non-NaN, finite, and not all zero.
|
static boolean |
MathArrays.verifyValues(double[] values,
int begin,
int length)
This method is used
to verify that the input parameters designate a subarray of positive length.
|
static boolean |
MathArrays.verifyValues(double[] values,
int begin,
int length,
boolean allowEmpty)
This method is used
to verify that the input parameters designate a subarray of positive length.
|
| Constructor and Description |
|---|
ResizableDoubleArray(int initialCapacity)
Creates an instance with the specified initial capacity.
|
ResizableDoubleArray(int initialCapacity,
double expansionFactor)
Creates an instance with the specified initial capacity
and expansion factor.
|
ResizableDoubleArray(int initialCapacity,
double expansionFactor,
double contractionCriterion)
Creates an instance with the specified initial capacity,
expansion factor, and contraction criteria.
|
ResizableDoubleArray(int initialCapacity,
double expansionFactor,
double contractionCriterion,
ResizableDoubleArray.ExpansionMode expansionMode,
double... data)
Creates an instance with the specified properties.
|
ResizableDoubleArray(int initialCapacity,
float expansionFactor)
Deprecated.
As of 3.1. Please use
ResizableDoubleArray.ResizableDoubleArray(int,double) instead. |
ResizableDoubleArray(int initialCapacity,
float expansionFactor,
float contractionCriteria)
Deprecated.
As of 3.1. Please use
ResizableDoubleArray.ResizableDoubleArray(int,double,double) instead. |
ResizableDoubleArray(int initialCapacity,
float expansionFactor,
float contractionCriteria,
int expansionMode)
Deprecated.
As of 3.1. Please use
ResizableDoubleArray.ResizableDoubleArray(int,double,double,ExpansionMode,double[])
instead. |
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