| 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.polynomials |
Univariate real polynomials implementations, seen as differentiable
univariate real functions.
|
| org.apache.commons.math3.analysis.solvers |
Root finding algorithms, for univariate real functions.
|
| org.apache.commons.math3.dfp |
Decimal floating point library for Java
|
| org.apache.commons.math3.distribution |
Implementations of common discrete and continuous distributions.
|
| org.apache.commons.math3.distribution.fitting |
Fitting of parameters against distributions.
|
| org.apache.commons.math3.exception |
Specialized exceptions for algorithms errors.
|
| org.apache.commons.math3.genetics |
This package provides Genetic Algorithms components and implementations.
|
| 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.ode.nonstiff |
This package provides classes to solve non-stiff Ordinary Differential Equations problems.
|
| 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.correlation |
Correlations/Covariance computations.
|
| org.apache.commons.math3.stat.inference |
Classes providing hypothesis testing.
|
| org.apache.commons.math3.util |
Convenience routines and common data structures used throughout the commons-math library.
|
| Constructor and Description |
|---|
FiniteDifferencesDifferentiator(int nbPoints,
double stepSize)
Build a differentiator with number of points and step size when independent variable is unbounded.
|
FiniteDifferencesDifferentiator(int nbPoints,
double stepSize,
double tLower,
double tUpper)
Build a differentiator with number of points and step size when independent variable is bounded.
|
| Constructor and Description |
|---|
BaseAbstractUnivariateIntegrator(double relativeAccuracy,
double absoluteAccuracy,
int minimalIterationCount,
int maximalIterationCount)
Construct an integrator with given accuracies and iteration counts.
|
BaseAbstractUnivariateIntegrator(int minimalIterationCount,
int maximalIterationCount)
Construct an integrator with given iteration counts.
|
IterativeLegendreGaussIntegrator(int n,
double relativeAccuracy,
double absoluteAccuracy,
int minimalIterationCount,
int maximalIterationCount)
Builds an integrator with given accuracies and iterations counts.
|
IterativeLegendreGaussIntegrator(int n,
int minimalIterationCount,
int maximalIterationCount)
Builds an integrator with given iteration counts.
|
LegendreGaussIntegrator(int n,
double relativeAccuracy,
double absoluteAccuracy,
int minimalIterationCount,
int maximalIterationCount)
Deprecated.
Build a Legendre-Gauss integrator with given accuracies and iterations counts.
|
MidPointIntegrator(double relativeAccuracy,
double absoluteAccuracy,
int minimalIterationCount,
int maximalIterationCount)
Build a midpoint integrator with given accuracies and iterations counts.
|
MidPointIntegrator(int minimalIterationCount,
int maximalIterationCount)
Build a midpoint integrator with given iteration counts.
|
RombergIntegrator(double relativeAccuracy,
double absoluteAccuracy,
int minimalIterationCount,
int maximalIterationCount)
Build a Romberg integrator with given accuracies and iterations counts.
|
RombergIntegrator(int minimalIterationCount,
int maximalIterationCount)
Build a Romberg integrator with given iteration counts.
|
SimpsonIntegrator(double relativeAccuracy,
double absoluteAccuracy,
int minimalIterationCount,
int maximalIterationCount)
Build a Simpson integrator with given accuracies and iterations counts.
|
SimpsonIntegrator(int minimalIterationCount,
int maximalIterationCount)
Build a Simpson integrator with given iteration counts.
|
TrapezoidIntegrator(double relativeAccuracy,
double absoluteAccuracy,
int minimalIterationCount,
int maximalIterationCount)
Build a trapezoid integrator with given accuracies and iterations counts.
|
TrapezoidIntegrator(int minimalIterationCount,
int maximalIterationCount)
Build a trapezoid integrator with given iteration counts.
|
| Modifier and Type | Method and Description |
|---|---|
protected static double[] |
DividedDifferenceInterpolator.computeDividedDifference(double[] x,
double[] y)
Return a copy of the divided difference array.
|
UnivariateFunction |
UnivariatePeriodicInterpolator.interpolate(double[] xval,
double[] yval)
Compute an interpolating function for the dataset.
|
PolynomialSplineFunction |
LinearInterpolator.interpolate(double[] x,
double[] y)
Computes a linear interpolating function for the data set.
|
PolynomialFunctionLagrangeForm |
NevilleInterpolator.interpolate(double[] x,
double[] y)
Computes an interpolating function for the data set.
|
PolynomialSplineFunction |
AkimaSplineInterpolator.interpolate(double[] xvals,
double[] yvals)
Computes an interpolating function for the data set.
|
PolynomialSplineFunction |
SplineInterpolator.interpolate(double[] x,
double[] y)
Computes an interpolating function for the data set.
|
PolynomialFunctionNewtonForm |
DividedDifferenceInterpolator.interpolate(double[] x,
double[] y)
Compute an interpolating function for the dataset.
|
PolynomialSplineFunction |
LoessInterpolator.interpolate(double[] xval,
double[] yval)
Compute an interpolating function by performing a loess fit
on the data at the original abscissae and then building a cubic spline
with a
SplineInterpolator
on the resulting fit. |
BicubicInterpolatingFunction |
BicubicInterpolator.interpolate(double[] xval,
double[] yval,
double[][] fval)
Compute an interpolating function for the dataset.
|
BicubicSplineInterpolatingFunction |
BicubicSplineInterpolator.interpolate(double[] xval,
double[] yval,
double[][] fval)
Deprecated.
Compute an interpolating function for the dataset.
|
BivariateFunction |
BivariateGridInterpolator.interpolate(double[] xval,
double[] yval,
double[][] fval)
Compute an interpolating function for the dataset.
|
TricubicInterpolatingFunction |
TricubicInterpolator.interpolate(double[] xval,
double[] yval,
double[] zval,
double[][][] fval)
Compute an interpolating function for the dataset.
|
TrivariateFunction |
TrivariateGridInterpolator.interpolate(double[] xval,
double[] yval,
double[] zval,
double[][][] fval)
Compute an interpolating function for the dataset.
|
TricubicSplineInterpolatingFunction |
TricubicSplineInterpolator.interpolate(double[] xval,
double[] yval,
double[] zval,
double[][][] fval)
Deprecated.
Compute an interpolating function for the dataset.
|
double[] |
LoessInterpolator.smooth(double[] xval,
double[] yval)
Compute a loess fit on the data at the original abscissae.
|
double[] |
LoessInterpolator.smooth(double[] xval,
double[] yval,
double[] weights)
Compute a weighted loess fit on the data at the original abscissae.
|
| Modifier and Type | Method and Description |
|---|---|
static double |
PolynomialFunctionLagrangeForm.evaluate(double[] x,
double[] y,
double z)
Evaluate the Lagrange polynomial using
Neville's Algorithm.
|
static boolean |
PolynomialFunctionLagrangeForm.verifyInterpolationArray(double[] x,
double[] y,
boolean abort)
Check that the interpolation arrays are valid.
|
| Constructor and Description |
|---|
PolynomialFunctionLagrangeForm(double[] x,
double[] y)
Construct a Lagrange polynomial with the given abscissas and function
values.
|
PolynomialSplineFunction(double[] knots,
PolynomialFunction[] polynomials)
Construct a polynomial spline function with the given segment delimiters
and interpolating polynomials.
|
| Constructor and Description |
|---|
BracketingNthOrderBrentSolver(double relativeAccuracy,
double absoluteAccuracy,
double functionValueAccuracy,
int maximalOrder)
Construct a solver.
|
BracketingNthOrderBrentSolver(double relativeAccuracy,
double absoluteAccuracy,
int maximalOrder)
Construct a solver.
|
BracketingNthOrderBrentSolver(double absoluteAccuracy,
int maximalOrder)
Construct a solver.
|
FieldBracketingNthOrderBrentSolver(T relativeAccuracy,
T absoluteAccuracy,
T functionValueAccuracy,
int maximalOrder)
Construct a solver.
|
| Constructor and Description |
|---|
BracketingNthOrderBrentSolverDFP(Dfp relativeAccuracy,
Dfp absoluteAccuracy,
Dfp functionValueAccuracy,
int maximalOrder)
Deprecated.
Construct a solver.
|
| Constructor and Description |
|---|
TriangularDistribution(double a,
double c,
double b)
Creates a triangular real distribution using the given lower limit,
upper limit, and mode.
|
TriangularDistribution(RandomGenerator rng,
double a,
double c,
double b)
Creates a triangular distribution.
|
| Constructor and Description |
|---|
MultivariateNormalMixtureExpectationMaximization(double[][] data)
Creates an object to fit a multivariate normal mixture model to data.
|
| Modifier and Type | Class and Description |
|---|---|
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.
|
| Modifier and Type | Method and Description |
|---|---|
void |
ListPopulation.setPopulationLimit(int populationLimit)
Sets the maximal population size.
|
| Constructor and Description |
|---|
FixedElapsedTime(long maxTime)
Create a new
FixedElapsedTime instance. |
FixedElapsedTime(long maxTime,
TimeUnit unit)
Create a new
FixedElapsedTime instance. |
FixedGenerationCount(int maxGenerations)
Create a new FixedGenerationCount instance.
|
| Modifier and Type | Class and Description |
|---|---|
class |
NonPositiveDefiniteMatrixException
Exception to be thrown when a positive definite matrix is expected.
|
| Modifier and Type | Method and Description |
|---|---|
protected void |
RealVector.checkIndices(int start,
int end)
Checks that the indices of a subvector are valid.
|
static void |
MatrixUtils.checkSubMatrixIndex(AnyMatrix m,
int startRow,
int endRow,
int startColumn,
int endColumn)
Check if submatrix ranges indices are valid.
|
protected void |
AbstractFieldMatrix.checkSubMatrixIndex(int startRow,
int endRow,
int startColumn,
int endColumn)
Check if submatrix ranges indices are valid.
|
void |
AbstractRealMatrix.copySubMatrix(int startRow,
int endRow,
int startColumn,
int endColumn,
double[][] destination)
Copy a submatrix.
|
void |
RealMatrix.copySubMatrix(int startRow,
int endRow,
int startColumn,
int endColumn,
double[][] destination)
Copy a submatrix.
|
void |
AbstractFieldMatrix.copySubMatrix(int startRow,
int endRow,
int startColumn,
int endColumn,
T[][] destination)
Copy a submatrix.
|
void |
FieldMatrix.copySubMatrix(int startRow,
int endRow,
int startColumn,
int endColumn,
T[][] destination)
Copy a submatrix.
|
BlockRealMatrix |
BlockRealMatrix.getSubMatrix(int startRow,
int endRow,
int startColumn,
int endColumn)
Gets a submatrix.
|
RealMatrix |
AbstractRealMatrix.getSubMatrix(int startRow,
int endRow,
int startColumn,
int endColumn)
Gets a submatrix.
|
FieldMatrix<T> |
AbstractFieldMatrix.getSubMatrix(int startRow,
int endRow,
int startColumn,
int endColumn)
Get a submatrix.
|
RealMatrix |
RealMatrix.getSubMatrix(int startRow,
int endRow,
int startColumn,
int endColumn)
Gets a submatrix.
|
FieldMatrix<T> |
BlockFieldMatrix.getSubMatrix(int startRow,
int endRow,
int startColumn,
int endColumn)
Get a submatrix.
|
FieldMatrix<T> |
FieldMatrix.getSubMatrix(int startRow,
int endRow,
int startColumn,
int endColumn)
Get a submatrix.
|
T |
Array2DRowFieldMatrix.walkInColumnOrder(FieldMatrixChangingVisitor<T> visitor,
int startRow,
int endRow,
int startColumn,
int endColumn)
Visit (and possibly change) some matrix entries in column order.
|
T |
AbstractFieldMatrix.walkInColumnOrder(FieldMatrixChangingVisitor<T> visitor,
int startRow,
int endRow,
int startColumn,
int endColumn)
Visit (and possibly change) some matrix entries in column order.
|
T |
FieldMatrix.walkInColumnOrder(FieldMatrixChangingVisitor<T> visitor,
int startRow,
int endRow,
int startColumn,
int endColumn)
Visit (and possibly change) some matrix entries in column order.
|
T |
Array2DRowFieldMatrix.walkInColumnOrder(FieldMatrixPreservingVisitor<T> visitor,
int startRow,
int endRow,
int startColumn,
int endColumn)
Visit (but don't change) some matrix entries in column order.
|
T |
AbstractFieldMatrix.walkInColumnOrder(FieldMatrixPreservingVisitor<T> visitor,
int startRow,
int endRow,
int startColumn,
int endColumn)
Visit (but don't change) some matrix entries in column order.
|
T |
FieldMatrix.walkInColumnOrder(FieldMatrixPreservingVisitor<T> visitor,
int startRow,
int endRow,
int startColumn,
int endColumn)
Visit (but don't change) some matrix entries in column order.
|
double |
AbstractRealMatrix.walkInColumnOrder(RealMatrixChangingVisitor visitor,
int startRow,
int endRow,
int startColumn,
int endColumn)
Visit (and possibly change) some matrix entries in column order.
|
double |
RealMatrix.walkInColumnOrder(RealMatrixChangingVisitor visitor,
int startRow,
int endRow,
int startColumn,
int endColumn)
Visit (and possibly change) some matrix entries in column order.
|
double |
Array2DRowRealMatrix.walkInColumnOrder(RealMatrixChangingVisitor visitor,
int startRow,
int endRow,
int startColumn,
int endColumn)
Visit (and possibly change) some matrix entries in column order.
|
double |
AbstractRealMatrix.walkInColumnOrder(RealMatrixPreservingVisitor visitor,
int startRow,
int endRow,
int startColumn,
int endColumn)
Visit (but don't change) some matrix entries in column order.
|
double |
RealMatrix.walkInColumnOrder(RealMatrixPreservingVisitor visitor,
int startRow,
int endRow,
int startColumn,
int endColumn)
Visit (but don't change) some matrix entries in column order.
|
double |
Array2DRowRealMatrix.walkInColumnOrder(RealMatrixPreservingVisitor visitor,
int startRow,
int endRow,
int startColumn,
int endColumn)
Visit (but don't change) some matrix entries in column order.
|
T |
SparseFieldVector.walkInDefaultOrder(FieldVectorChangingVisitor<T> visitor,
int start,
int end)
Visits (and possibly alters) some entries of this vector in default order
(increasing index).
|
T |
ArrayFieldVector.walkInDefaultOrder(FieldVectorChangingVisitor<T> visitor,
int start,
int end)
Visits (and possibly alters) some entries of this vector in default order
(increasing index).
|
T |
SparseFieldVector.walkInDefaultOrder(FieldVectorPreservingVisitor<T> visitor,
int start,
int end)
Visits (but does not alter) some entries of this vector in default order
(increasing index).
|
T |
ArrayFieldVector.walkInDefaultOrder(FieldVectorPreservingVisitor<T> visitor,
int start,
int end)
Visits (but does not alter) some entries of this vector in default order
(increasing index).
|
double |
RealVector.walkInDefaultOrder(RealVectorChangingVisitor visitor,
int start,
int end)
Visits (and possibly alters) some entries of this vector in default order
(increasing index).
|
double |
ArrayRealVector.walkInDefaultOrder(RealVectorChangingVisitor visitor,
int start,
int end)
Visits (and possibly alters) some entries of this vector in default order
(increasing index).
|
double |
RealVector.walkInDefaultOrder(RealVectorPreservingVisitor visitor,
int start,
int end)
Visits (but does not alter) some entries of this vector in default order
(increasing index).
|
double |
ArrayRealVector.walkInDefaultOrder(RealVectorPreservingVisitor visitor,
int start,
int end)
Visits (but does not alter) some entries of this vector in default order
(increasing index).
|
T |
AbstractFieldMatrix.walkInOptimizedOrder(FieldMatrixChangingVisitor<T> visitor,
int startRow,
int endRow,
int startColumn,
int endColumn)
Visit (and possibly change) some matrix entries using the fastest possible order.
|
T |
BlockFieldMatrix.walkInOptimizedOrder(FieldMatrixChangingVisitor<T> visitor,
int startRow,
int endRow,
int startColumn,
int endColumn)
Visit (and possibly change) some matrix entries using the fastest possible order.
|
T |
FieldMatrix.walkInOptimizedOrder(FieldMatrixChangingVisitor<T> visitor,
int startRow,
int endRow,
int startColumn,
int endColumn)
Visit (and possibly change) some matrix entries using the fastest possible order.
|
T |
AbstractFieldMatrix.walkInOptimizedOrder(FieldMatrixPreservingVisitor<T> visitor,
int startRow,
int endRow,
int startColumn,
int endColumn)
Visit (but don't change) some matrix entries using the fastest possible order.
|
T |
BlockFieldMatrix.walkInOptimizedOrder(FieldMatrixPreservingVisitor<T> visitor,
int startRow,
int endRow,
int startColumn,
int endColumn)
Visit (but don't change) some matrix entries using the fastest possible order.
|
T |
FieldMatrix.walkInOptimizedOrder(FieldMatrixPreservingVisitor<T> visitor,
int startRow,
int endRow,
int startColumn,
int endColumn)
Visit (but don't change) some matrix entries using the fastest possible order.
|
T |
SparseFieldVector.walkInOptimizedOrder(FieldVectorChangingVisitor<T> visitor,
int start,
int end)
Visits (and possibly change) some entries of this vector in optimized
order.
|
T |
ArrayFieldVector.walkInOptimizedOrder(FieldVectorChangingVisitor<T> visitor,
int start,
int end)
Visits (and possibly change) some entries of this vector in optimized
order.
|
T |
SparseFieldVector.walkInOptimizedOrder(FieldVectorPreservingVisitor<T> visitor,
int start,
int end)
Visits (but does not alter) some entries of this vector in optimized
order.
|
T |
ArrayFieldVector.walkInOptimizedOrder(FieldVectorPreservingVisitor<T> visitor,
int start,
int end)
Visits (but does not alter) some entries of this vector in optimized
order.
|
double |
BlockRealMatrix.walkInOptimizedOrder(RealMatrixChangingVisitor visitor,
int startRow,
int endRow,
int startColumn,
int endColumn)
Visit (and possibly change) some matrix entries using the fastest possible order.
|
double |
AbstractRealMatrix.walkInOptimizedOrder(RealMatrixChangingVisitor visitor,
int startRow,
int endRow,
int startColumn,
int endColumn)
Visit (and possibly change) some matrix entries using the fastest possible order.
|
double |
RealMatrix.walkInOptimizedOrder(RealMatrixChangingVisitor visitor,
int startRow,
int endRow,
int startColumn,
int endColumn)
Visit (and possibly change) some matrix entries using the fastest possible order.
|
double |
BlockRealMatrix.walkInOptimizedOrder(RealMatrixPreservingVisitor visitor,
int startRow,
int endRow,
int startColumn,
int endColumn)
Visit (but don't change) some matrix entries using the fastest possible order.
|
double |
AbstractRealMatrix.walkInOptimizedOrder(RealMatrixPreservingVisitor visitor,
int startRow,
int endRow,
int startColumn,
int endColumn)
Visit (but don't change) some matrix entries using the fastest possible order.
|
double |
RealMatrix.walkInOptimizedOrder(RealMatrixPreservingVisitor visitor,
int startRow,
int endRow,
int startColumn,
int endColumn)
Visit (but don't change) some matrix entries using the fastest possible order.
|
double |
RealVector.walkInOptimizedOrder(RealVectorChangingVisitor visitor,
int start,
int end)
Visits (and possibly change) some entries of this vector in optimized
order.
|
double |
ArrayRealVector.walkInOptimizedOrder(RealVectorChangingVisitor visitor,
int start,
int end)
Visits (and possibly change) some entries of this vector in optimized
order.
|
double |
RealVector.walkInOptimizedOrder(RealVectorPreservingVisitor visitor,
int start,
int end)
Visits (but does not alter) some entries of this vector in optimized
order.
|
double |
ArrayRealVector.walkInOptimizedOrder(RealVectorPreservingVisitor visitor,
int start,
int end)
Visits (but does not alter) some entries of this vector in optimized
order.
|
T |
Array2DRowFieldMatrix.walkInRowOrder(FieldMatrixChangingVisitor<T> visitor,
int startRow,
int endRow,
int startColumn,
int endColumn)
Visit (and possibly change) some matrix entries in row order.
|
T |
AbstractFieldMatrix.walkInRowOrder(FieldMatrixChangingVisitor<T> visitor,
int startRow,
int endRow,
int startColumn,
int endColumn)
Visit (and possibly change) some matrix entries in row order.
|
T |
BlockFieldMatrix.walkInRowOrder(FieldMatrixChangingVisitor<T> visitor,
int startRow,
int endRow,
int startColumn,
int endColumn)
Visit (and possibly change) some matrix entries in row order.
|
T |
FieldMatrix.walkInRowOrder(FieldMatrixChangingVisitor<T> visitor,
int startRow,
int endRow,
int startColumn,
int endColumn)
Visit (and possibly change) some matrix entries in row order.
|
T |
Array2DRowFieldMatrix.walkInRowOrder(FieldMatrixPreservingVisitor<T> visitor,
int startRow,
int endRow,
int startColumn,
int endColumn)
Visit (but don't change) some matrix entries in row order.
|
T |
AbstractFieldMatrix.walkInRowOrder(FieldMatrixPreservingVisitor<T> visitor,
int startRow,
int endRow,
int startColumn,
int endColumn)
Visit (but don't change) some matrix entries in row order.
|
T |
BlockFieldMatrix.walkInRowOrder(FieldMatrixPreservingVisitor<T> visitor,
int startRow,
int endRow,
int startColumn,
int endColumn)
Visit (but don't change) some matrix entries in row order.
|
T |
FieldMatrix.walkInRowOrder(FieldMatrixPreservingVisitor<T> visitor,
int startRow,
int endRow,
int startColumn,
int endColumn)
Visit (but don't change) some matrix entries in row order.
|
double |
BlockRealMatrix.walkInRowOrder(RealMatrixChangingVisitor visitor,
int startRow,
int endRow,
int startColumn,
int endColumn)
Visit (and possibly change) some matrix entries in row order.
|
double |
AbstractRealMatrix.walkInRowOrder(RealMatrixChangingVisitor visitor,
int startRow,
int endRow,
int startColumn,
int endColumn)
Visit (and possibly change) some matrix entries in row order.
|
double |
RealMatrix.walkInRowOrder(RealMatrixChangingVisitor visitor,
int startRow,
int endRow,
int startColumn,
int endColumn)
Visit (and possibly change) some matrix entries in row order.
|
double |
Array2DRowRealMatrix.walkInRowOrder(RealMatrixChangingVisitor visitor,
int startRow,
int endRow,
int startColumn,
int endColumn)
Visit (and possibly change) some matrix entries in row order.
|
double |
BlockRealMatrix.walkInRowOrder(RealMatrixPreservingVisitor visitor,
int startRow,
int endRow,
int startColumn,
int endColumn)
Visit (but don't change) some matrix entries in row order.
|
double |
AbstractRealMatrix.walkInRowOrder(RealMatrixPreservingVisitor visitor,
int startRow,
int endRow,
int startColumn,
int endColumn)
Visit (but don't change) some matrix entries in row order.
|
double |
RealMatrix.walkInRowOrder(RealMatrixPreservingVisitor visitor,
int startRow,
int endRow,
int startColumn,
int endColumn)
Visit (but don't change) some matrix entries in row order.
|
double |
Array2DRowRealMatrix.walkInRowOrder(RealMatrixPreservingVisitor visitor,
int startRow,
int endRow,
int startColumn,
int endColumn)
Visit (but don't change) some matrix entries in row order.
|
| Constructor and Description |
|---|
FuzzyKMeansClusterer(int k,
double fuzziness)
Creates a new instance of a FuzzyKMeansClusterer.
|
FuzzyKMeansClusterer(int k,
double fuzziness,
int maxIterations,
DistanceMeasure measure)
Creates a new instance of a FuzzyKMeansClusterer.
|
FuzzyKMeansClusterer(int k,
double fuzziness,
int maxIterations,
DistanceMeasure measure,
double epsilon,
RandomGenerator random)
Creates a new instance of a FuzzyKMeansClusterer.
|
| Modifier and Type | Method and Description |
|---|---|
abstract void |
AbstractIntegrator.integrate(ExpandableStatefulODE equations,
double t)
Integrate a set of differential equations up to the given time.
|
FieldODEStateAndDerivative<T> |
FirstOrderFieldIntegrator.integrate(FieldExpandableODE<T> equations,
FieldODEState<T> initialState,
T finalTime)
Integrate the differential equations up to the given time.
|
double |
FirstOrderIntegrator.integrate(FirstOrderDifferentialEquations equations,
double t0,
double[] y0,
double t,
double[] y)
Integrate the differential equations up to the given time.
|
double |
AbstractIntegrator.integrate(FirstOrderDifferentialEquations equations,
double t0,
double[] y0,
double t,
double[] y)
Integrate the differential equations up to the given time.
|
protected void |
AbstractIntegrator.sanityChecks(ExpandableStatefulODE equations,
double t)
Check the integration span.
|
protected void |
AbstractFieldIntegrator.sanityChecks(FieldODEState<T> eqn,
T t)
Check the integration span.
|
protected void |
MultistepIntegrator.start(double t0,
double[] y0,
double t)
Start the integration.
|
protected void |
MultistepFieldIntegrator.start(FieldExpandableODE<T> equations,
FieldODEState<T> initialState,
T t)
Start the integration.
|
| Constructor and Description |
|---|
MultistepFieldIntegrator(Field<T> field,
String name,
int nSteps,
int order,
double minStep,
double maxStep,
double scalAbsoluteTolerance,
double scalRelativeTolerance)
Build a multistep integrator with the given stepsize bounds.
|
MultistepIntegrator(String name,
int nSteps,
int order,
double minStep,
double maxStep,
double scalAbsoluteTolerance,
double scalRelativeTolerance)
Build a multistep integrator with the given stepsize bounds.
|
| Modifier and Type | Method and Description |
|---|---|
protected double |
AdaptiveStepsizeIntegrator.filterStep(double h,
boolean forward,
boolean acceptSmall)
Filter the integration step.
|
protected T |
AdaptiveStepsizeFieldIntegrator.filterStep(T h,
boolean forward,
boolean acceptSmall)
Filter the integration step.
|
abstract void |
AdamsIntegrator.integrate(ExpandableStatefulODE equations,
double t)
Integrate a set of differential equations up to the given time.
|
abstract void |
AdaptiveStepsizeIntegrator.integrate(ExpandableStatefulODE equations,
double t)
Integrate a set of differential equations up to the given time.
|
void |
AdamsMoultonIntegrator.integrate(ExpandableStatefulODE equations,
double t)
Integrate a set of differential equations up to the given time.
|
void |
EmbeddedRungeKuttaIntegrator.integrate(ExpandableStatefulODE equations,
double t)
Integrate a set of differential equations up to the given time.
|
void |
AdamsBashforthIntegrator.integrate(ExpandableStatefulODE equations,
double t)
Integrate a set of differential equations up to the given time.
|
void |
RungeKuttaIntegrator.integrate(ExpandableStatefulODE equations,
double t)
Integrate a set of differential equations up to the given time.
|
void |
GraggBulirschStoerIntegrator.integrate(ExpandableStatefulODE equations,
double t)
Integrate a set of differential equations up to the given time.
|
FieldODEStateAndDerivative<T> |
RungeKuttaFieldIntegrator.integrate(FieldExpandableODE<T> equations,
FieldODEState<T> initialState,
T finalTime)
Integrate the differential equations up to the given time.
|
FieldODEStateAndDerivative<T> |
EmbeddedRungeKuttaFieldIntegrator.integrate(FieldExpandableODE<T> equations,
FieldODEState<T> initialState,
T finalTime)
Integrate the differential equations up to the given time.
|
FieldODEStateAndDerivative<T> |
AdamsBashforthFieldIntegrator.integrate(FieldExpandableODE<T> equations,
FieldODEState<T> initialState,
T finalTime)
Integrate the differential equations up to the given time.
|
FieldODEStateAndDerivative<T> |
AdamsMoultonFieldIntegrator.integrate(FieldExpandableODE<T> equations,
FieldODEState<T> initialState,
T finalTime)
Integrate the differential equations up to the given time.
|
abstract FieldODEStateAndDerivative<T> |
AdamsFieldIntegrator.integrate(FieldExpandableODE<T> equations,
FieldODEState<T> initialState,
T finalTime)
Integrate the differential equations up to the given time.
|
protected void |
AdaptiveStepsizeIntegrator.sanityChecks(ExpandableStatefulODE equations,
double t)
Check the integration span.
|
protected void |
AdaptiveStepsizeFieldIntegrator.sanityChecks(FieldODEState<T> eqn,
T t)
Check the integration span.
|
| Constructor and Description |
|---|
AdamsBashforthFieldIntegrator(Field<T> field,
int nSteps,
double minStep,
double maxStep,
double scalAbsoluteTolerance,
double scalRelativeTolerance)
Build an Adams-Bashforth integrator with the given order and step control parameters.
|
AdamsBashforthIntegrator(int nSteps,
double minStep,
double maxStep,
double scalAbsoluteTolerance,
double scalRelativeTolerance)
Build an Adams-Bashforth integrator with the given order and step control parameters.
|
AdamsFieldIntegrator(Field<T> field,
String name,
int nSteps,
int order,
double minStep,
double maxStep,
double scalAbsoluteTolerance,
double scalRelativeTolerance)
Build an Adams integrator with the given order and step control parameters.
|
AdamsIntegrator(String name,
int nSteps,
int order,
double minStep,
double maxStep,
double scalAbsoluteTolerance,
double scalRelativeTolerance)
Build an Adams integrator with the given order and step control parameters.
|
AdamsMoultonFieldIntegrator(Field<T> field,
int nSteps,
double minStep,
double maxStep,
double scalAbsoluteTolerance,
double scalRelativeTolerance)
Build an Adams-Moulton integrator with the given order and error control parameters.
|
AdamsMoultonIntegrator(int nSteps,
double minStep,
double maxStep,
double scalAbsoluteTolerance,
double scalRelativeTolerance)
Build an Adams-Moulton integrator with the given order and error control parameters.
|
| Modifier and Type | Method and Description |
|---|---|
static double |
Gamma.logGamma1p(double x)
Returns the value of log Γ(1 + x) for -0.5 ≤ x ≤ 1.5.
|
| Modifier and Type | Method and Description |
|---|---|
static double |
StatUtils.varianceDifference(double[] sample1,
double[] sample2,
double meanDifference)
Returns the variance of the (signed) differences between corresponding elements of the
input arrays -- i.e., var(sample1[i] - sample2[i]).
|
| Modifier and Type | Method and Description |
|---|---|
double |
StorelessCovariance.getCovariance(int xIndex,
int yIndex)
Get the covariance for an individual element of the covariance matrix.
|
RealMatrix |
StorelessCovariance.getCovarianceMatrix()
Returns the covariance matrix
|
double[][] |
StorelessCovariance.getData()
Return the covariance matrix as two-dimensional array.
|
| Modifier and Type | Method and Description |
|---|---|
static double |
TestUtils.homoscedasticT(double[] sample1,
double[] sample2) |
double |
TTest.homoscedasticT(double[] sample1,
double[] sample2)
Computes a 2-sample t statistic, under the hypothesis of equal
subpopulation variances.
|
static double |
TestUtils.homoscedasticT(StatisticalSummary sampleStats1,
StatisticalSummary sampleStats2) |
double |
TTest.homoscedasticT(StatisticalSummary sampleStats1,
StatisticalSummary sampleStats2)
Computes a 2-sample t statistic, comparing the means of the datasets
described by two
StatisticalSummary instances, under the
assumption of equal subpopulation variances. |
static double |
TestUtils.homoscedasticTTest(double[] sample1,
double[] sample2) |
double |
TTest.homoscedasticTTest(double[] sample1,
double[] sample2)
Returns the observed significance level, or
p-value, associated with a two-sample, two-tailed t-test
comparing the means of the input arrays, under the assumption that
the two samples are drawn from subpopulations with equal variances.
|
static boolean |
TestUtils.homoscedasticTTest(double[] sample1,
double[] sample2,
double alpha) |
boolean |
TTest.homoscedasticTTest(double[] sample1,
double[] sample2,
double alpha)
Performs a
two-sided t-test evaluating the null hypothesis that
sample1
and sample2 are drawn from populations with the same mean,
with significance level alpha, assuming that the
subpopulation variances are equal. |
static double |
TestUtils.homoscedasticTTest(StatisticalSummary sampleStats1,
StatisticalSummary sampleStats2) |
double |
TTest.homoscedasticTTest(StatisticalSummary sampleStats1,
StatisticalSummary sampleStats2)
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, under the hypothesis of equal subpopulation variances.
|
static double |
TestUtils.pairedT(double[] sample1,
double[] sample2) |
double |
TTest.pairedT(double[] sample1,
double[] sample2)
Computes a paired, 2-sample t-statistic based on the data in the input
arrays.
|
static double |
TestUtils.pairedTTest(double[] sample1,
double[] sample2) |
double |
TTest.pairedTTest(double[] sample1,
double[] sample2)
Returns the observed significance level, or
p-value, associated with a paired, two-sample, two-tailed t-test
based on the data in the input arrays.
|
static boolean |
TestUtils.pairedTTest(double[] sample1,
double[] sample2,
double alpha) |
boolean |
TTest.pairedTTest(double[] sample1,
double[] sample2,
double alpha)
Performs a paired t-test evaluating the null hypothesis that the
mean of the paired differences between
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. |
static double |
TestUtils.t(double[] sample1,
double[] sample2) |
double |
TTest.t(double[] sample1,
double[] sample2)
Computes a 2-sample t statistic, without the hypothesis of equal
subpopulation variances.
|
static double |
TestUtils.t(double mu,
double[] observed) |
double |
TTest.t(double mu,
double[] observed)
Computes a
t statistic given observed values and a comparison constant.
|
static double |
TestUtils.t(double mu,
StatisticalSummary sampleStats) |
double |
TTest.t(double mu,
StatisticalSummary sampleStats)
|
static double |
TestUtils.t(StatisticalSummary sampleStats1,
StatisticalSummary sampleStats2) |
double |
TTest.t(StatisticalSummary sampleStats1,
StatisticalSummary sampleStats2)
Computes a 2-sample t statistic , comparing the means of the datasets
described by two
StatisticalSummary instances, without the
assumption of equal subpopulation variances. |
static double |
TestUtils.tTest(double[] sample1,
double[] sample2) |
double |
TTest.tTest(double[] sample1,
double[] sample2)
Returns the observed significance level, or
p-value, associated with a two-sample, two-tailed t-test
comparing the means of the input arrays.
|
static boolean |
TestUtils.tTest(double[] sample1,
double[] sample2,
double alpha) |
boolean |
TTest.tTest(double[] sample1,
double[] sample2,
double alpha)
Performs a
two-sided t-test evaluating the null hypothesis that
sample1
and sample2 are drawn from populations with the same mean,
with significance level alpha. |
static double |
TestUtils.tTest(double mu,
double[] sample) |
double |
TTest.tTest(double mu,
double[] sample)
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. |
static boolean |
TestUtils.tTest(double mu,
double[] sample,
double alpha) |
boolean |
TTest.tTest(double mu,
double[] sample,
double alpha)
Performs a
two-sided t-test evaluating the null hypothesis that the mean of the population from
which
sample is drawn equals mu. |
static double |
TestUtils.tTest(double mu,
StatisticalSummary sampleStats) |
double |
TTest.tTest(double mu,
StatisticalSummary sampleStats)
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 constant mu. |
static boolean |
TestUtils.tTest(double mu,
StatisticalSummary sampleStats,
double alpha) |
boolean |
TTest.tTest(double mu,
StatisticalSummary sampleStats,
double alpha)
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 equals mu. |
static double |
TestUtils.tTest(StatisticalSummary sampleStats1,
StatisticalSummary sampleStats2) |
double |
TTest.tTest(StatisticalSummary sampleStats1,
StatisticalSummary sampleStats2)
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.
|
static boolean |
TestUtils.tTest(StatisticalSummary sampleStats1,
StatisticalSummary sampleStats2,
double alpha) |
boolean |
TTest.tTest(StatisticalSummary sampleStats1,
StatisticalSummary sampleStats2,
double alpha)
Performs a
two-sided t-test evaluating the null hypothesis that
sampleStats1 and sampleStats2 describe
datasets drawn from populations with the same mean, with significance
level alpha. |
| Modifier and Type | Method and Description |
|---|---|
protected void |
ResizableDoubleArray.checkContractExpand(double contraction,
double expansion)
Checks the expansion factor and the contraction criterion and raises
an exception if the contraction criterion is smaller than the
expansion criterion.
|
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