Uses of Interface
org.apache.commons.math4.legacy.linear.RealMatrix

Packages that use RealMatrix

Package	Description
org.apache.commons.math4.legacy.distribution	Implementations of probability distributions.
org.apache.commons.math4.legacy.filter	Implementations of common discrete-time linear filters.
org.apache.commons.math4.legacy.fitting.leastsquares	This package provides algorithms that minimize the residuals between observations and model values.
org.apache.commons.math4.legacy.linear	Linear algebra support.
org.apache.commons.math4.legacy.ml.clustering	Clustering algorithms.
org.apache.commons.math4.legacy.optim.nonlinear.scalar	Algorithms for optimizing a scalar function.
org.apache.commons.math4.legacy.optim.nonlinear.scalar.noderiv	This package provides optimization algorithms that do not require derivatives.
org.apache.commons.math4.legacy.random	This package contains functionality related to random numbers.
org.apache.commons.math4.legacy.stat.correlation	Correlations/Covariance computations.
org.apache.commons.math4.legacy.stat.descriptive	Generic univariate summary statistic objects.
org.apache.commons.math4.legacy.stat.descriptive.moment	Summary statistics based on moments.
org.apache.commons.math4.legacy.stat.regression	Statistical routines involving multivariate data.

Uses of RealMatrix in org.apache.commons.math4.legacy.distribution

Methods in org.apache.commons.math4.legacy.distribution that return RealMatrix

Modifier and Type	Method	Description
RealMatrix	MultivariateNormalDistribution.getCovariances()	Gets the covariance matrix.

Uses of RealMatrix in org.apache.commons.math4.legacy.filter

Methods in org.apache.commons.math4.legacy.filter that return RealMatrix

Modifier and Type	Method	Description
RealMatrix	DefaultProcessModel.getControlMatrix()	Returns the control matrix.
RealMatrix	ProcessModel.getControlMatrix()	Returns the control matrix.
RealMatrix	KalmanFilter.getErrorCovarianceMatrix()	Returns a copy of the current error covariance matrix.
RealMatrix	DefaultProcessModel.getInitialErrorCovariance()	Returns the initial error covariance matrix.
RealMatrix	ProcessModel.getInitialErrorCovariance()	Returns the initial error covariance matrix.
RealMatrix	DefaultMeasurementModel.getMeasurementMatrix()	Returns the measurement matrix.
RealMatrix	MeasurementModel.getMeasurementMatrix()	Returns the measurement matrix.
RealMatrix	DefaultMeasurementModel.getMeasurementNoise()	Returns the measurement noise matrix.
RealMatrix	MeasurementModel.getMeasurementNoise()	Returns the measurement noise matrix.
RealMatrix	DefaultProcessModel.getProcessNoise()	Returns the process noise matrix.
RealMatrix	ProcessModel.getProcessNoise()	Returns the process noise matrix.
RealMatrix	DefaultProcessModel.getStateTransitionMatrix()	Returns the state transition matrix.
RealMatrix	ProcessModel.getStateTransitionMatrix()	Returns the state transition matrix.

Constructors in org.apache.commons.math4.legacy.filter with parameters of type RealMatrix

Constructor	Description
DefaultMeasurementModel(RealMatrix measMatrix, RealMatrix measNoise)	Create a new MeasurementModel, taking RealMatrix objects as input parameters for the respective measurement matrix and noise.
DefaultProcessModel(RealMatrix stateTransition, RealMatrix control, RealMatrix processNoise, RealVector initialStateEstimate, RealMatrix initialErrorCovariance)	Create a new ProcessModel, taking double arrays as input parameters.

Uses of RealMatrix in org.apache.commons.math4.legacy.fitting.leastsquares

Methods in org.apache.commons.math4.legacy.fitting.leastsquares that return RealMatrix

Modifier and Type	Method	Description
RealMatrix	ValueAndJacobianFunction.computeJacobian(double[] params)	Compute the Jacobian.
RealMatrix	AbstractEvaluation.getCovariances(double threshold)	Get the covariance matrix of the optimized parameters.
RealMatrix	LeastSquaresProblem.Evaluation.getCovariances(double threshold)	Get the covariance matrix of the optimized parameters.
RealMatrix	LeastSquaresProblem.Evaluation.getJacobian()	Get the weighted Jacobian matrix.

Methods in org.apache.commons.math4.legacy.fitting.leastsquares that return types with arguments of type RealMatrix

Modifier and Type	Method	Description
Pair<RealVector,RealMatrix>	DifferentiatorVectorMultivariateJacobianFunction.value(RealVector point)	Compute the function value and its Jacobian.
Pair<RealVector,RealMatrix>	MultivariateJacobianFunction.value(RealVector point)	Compute the function value and its Jacobian.

Methods in org.apache.commons.math4.legacy.fitting.leastsquares with parameters of type RealMatrix

Modifier and Type	Method	Description
static LeastSquaresProblem	LeastSquaresFactory.create(MultivariateVectorFunction model, MultivariateMatrixFunction jacobian, double[] observed, double[] start, RealMatrix weight, ConvergenceChecker<LeastSquaresProblem.Evaluation> checker, int maxEvaluations, int maxIterations)	Create a LeastSquaresProblem from the given elements.
static LeastSquaresProblem	LeastSquaresFactory.create(MultivariateJacobianFunction model, RealVector observed, RealVector start, RealMatrix weight, ConvergenceChecker<LeastSquaresProblem.Evaluation> checker, int maxEvaluations, int maxIterations)	Create a LeastSquaresProblem from the given elements.
static LeastSquaresProblem	LeastSquaresFactory.create(MultivariateJacobianFunction model, RealVector observed, RealVector start, RealMatrix weight, ConvergenceChecker<LeastSquaresProblem.Evaluation> checker, int maxEvaluations, int maxIterations, boolean lazyEvaluation, ParameterValidator paramValidator)	Create a LeastSquaresProblem from the given elements.
protected abstract RealVector	GaussNewtonOptimizer.Decomposition.solve(RealMatrix jacobian, RealVector residuals)	Solve the linear least squares problem Jx=r.
LeastSquaresBuilder	LeastSquaresBuilder.weight(RealMatrix newWeight)	Configure the weight matrix.
static LeastSquaresProblem	LeastSquaresFactory.weightMatrix(LeastSquaresProblem problem, RealMatrix weights)	Apply a dense weight matrix to the LeastSquaresProblem.

Uses of RealMatrix in org.apache.commons.math4.legacy.linear

Subinterfaces of RealMatrix in org.apache.commons.math4.legacy.linear

Modifier and Type	Interface	Description
interface	SparseRealMatrix	Marker interface for RealMatrix implementations that require sparse backing storage

Classes in org.apache.commons.math4.legacy.linear that implement RealMatrix

Modifier and Type	Class	Description
class	AbstractRealMatrix	Basic implementation of RealMatrix methods regardless of the underlying storage.
class	Array2DRowRealMatrix	Implementation of RealMatrix using a double[][] array to store entries.
class	BlockRealMatrix	Cache-friendly implementation of RealMatrix using a flat arrays to store square blocks of the matrix.
class	DiagonalMatrix	Implementation of a diagonal matrix.
class	OpenMapRealMatrix	Sparse matrix implementation based on an open addressed map.

Methods in org.apache.commons.math4.legacy.linear that return RealMatrix

Modifier and Type	Method	Description
RealMatrix	AbstractRealMatrix.add(RealMatrix m)	Returns the sum of this and m.
RealMatrix	RealMatrix.add(RealMatrix m)	Returns the sum of this and m.
static RealMatrix	MatrixUtils.blockInverse(RealMatrix m, int splitIndex)	Computes the inverse of the given matrix by splitting it into 4 sub-matrices.
abstract RealMatrix	AbstractRealMatrix.copy()	Returns a (deep) copy of this.
RealMatrix	Array2DRowRealMatrix.copy()	Returns a (deep) copy of this.
RealMatrix	DiagonalMatrix.copy()	Returns a (deep) copy of this.
RealMatrix	RealMatrix.copy()	Returns a (deep) copy of this.
static RealMatrix	MatrixUtils.createColumnRealMatrix(double[] columnData)	Creates a column RealMatrix using the data from the input array.
abstract RealMatrix	AbstractRealMatrix.createMatrix(int rowDimension, int columnDimension)	Create a new RealMatrix of the same type as the instance with the supplied row and column dimensions.
RealMatrix	Array2DRowRealMatrix.createMatrix(int rowDimension, int columnDimension)	Create a new RealMatrix of the same type as the instance with the supplied row and column dimensions.
RealMatrix	DiagonalMatrix.createMatrix(int rowDimension, int columnDimension)	Create a new RealMatrix of the same type as the instance with the supplied row and column dimensions.
RealMatrix	RealMatrix.createMatrix(int rowDimension, int columnDimension)	Create a new RealMatrix of the same type as the instance with the supplied row and column dimensions.
static RealMatrix	MatrixUtils.createRealIdentityMatrix(int dimension)	Returns dimension x dimension identity matrix.
static RealMatrix	MatrixUtils.createRealMatrix(double[][] data)	Returns a RealMatrix whose entries are the values in the the input array.
static RealMatrix	MatrixUtils.createRealMatrix(int rows, int columns)	Returns a RealMatrix with specified dimensions.
static RealMatrix	MatrixUtils.createRealMatrixWithDiagonal(double[] diagonal)	Creates a dense matrix with the specified diagonal elements.
static RealMatrix	MatrixUtils.createRowRealMatrix(double[] rowData)	Create a row RealMatrix using the data from the input array.
RealMatrix	AbstractRealMatrix.getColumnMatrix(int column)	Get the entries at the given column index as a column matrix.
RealMatrix	RealMatrix.getColumnMatrix(int column)	Get the entries at the given column index as a column matrix.
RealMatrix	SingularValueDecomposition.getCovariance(double minSingularValue)	Returns the n × n covariance matrix.
RealMatrix	EigenDecomposition.getD()	Gets the block diagonal matrix D of the decomposition.
RealMatrix	QRDecomposition.getH()	Returns the Householder reflector vectors.
RealMatrix	DecompositionSolver.getInverse()	Get the pseudo-inverse of the decomposed matrix.
RealMatrix	CholeskyDecomposition.getL()	Returns the matrix L of the decomposition.
RealMatrix	LUDecomposition.getL()	Returns the matrix L of the decomposition.
RealMatrix	CholeskyDecomposition.getLT()	Returns the transpose of the matrix L of the decomposition.
RealMatrix	LUDecomposition.getP()	Returns the P rows permutation matrix.
RealMatrix	RRQRDecomposition.getP()	Returns the pivot matrix, P, used in the QR Decomposition of matrix A such that AP = QR.
RealMatrix	QRDecomposition.getQ()	Returns the matrix Q of the decomposition.
RealMatrix	QRDecomposition.getQT()	Returns the transpose of the matrix Q of the decomposition.
RealMatrix	QRDecomposition.getR()	Returns the matrix R of the decomposition.
RealMatrix	RectangularCholeskyDecomposition.getRootMatrix()	Get the root of the covariance matrix.
RealMatrix	AbstractRealMatrix.getRowMatrix(int row)	Get the entries at the given row index as a row matrix.
RealMatrix	RealMatrix.getRowMatrix(int row)	Get the entries at the given row index as a row matrix.
RealMatrix	SingularValueDecomposition.getS()	Returns the diagonal matrix Σ of the decomposition.
RealMatrix	EigenDecomposition.getSquareRoot()	Computes the square-root of the matrix.
RealMatrix	AbstractRealMatrix.getSubMatrix(int[] selectedRows, int[] selectedColumns)	Gets a submatrix.
RealMatrix	AbstractRealMatrix.getSubMatrix(int startRow, int endRow, int startColumn, int endColumn)	Gets a submatrix.
RealMatrix	Array2DRowRealMatrix.getSubMatrix(int startRow, int endRow, int startColumn, int endColumn)	Gets a submatrix.
RealMatrix	RealMatrix.getSubMatrix(int[] selectedRows, int[] selectedColumns)	Gets a submatrix.
RealMatrix	RealMatrix.getSubMatrix(int startRow, int endRow, int startColumn, int endColumn)	Gets a submatrix.
RealMatrix	LUDecomposition.getU()	Returns the matrix U of the decomposition.
RealMatrix	SingularValueDecomposition.getU()	Returns the matrix U of the decomposition.
RealMatrix	SingularValueDecomposition.getUT()	Returns the transpose of the matrix U of the decomposition.
RealMatrix	EigenDecomposition.getV()	Gets the matrix V of the decomposition.
RealMatrix	SingularValueDecomposition.getV()	Returns the matrix V of the decomposition.
RealMatrix	EigenDecomposition.getVT()	Gets the transpose of the matrix V of the decomposition.
RealMatrix	SingularValueDecomposition.getVT()	Returns the transpose of the matrix V of the decomposition.
static RealMatrix	MatrixUtils.inverse(RealMatrix matrix)	Computes the inverse of the given matrix.
static RealMatrix	MatrixUtils.inverse(RealMatrix matrix, double threshold)	Computes the inverse of the given matrix.
RealMatrix	AbstractRealMatrix.multiply(RealMatrix m)	Returns the result of postmultiplying this by m.
RealMatrix	DiagonalMatrix.multiply(RealMatrix m)	Returns the result of postmultiplying this by m.
RealMatrix	OpenMapRealMatrix.multiply(RealMatrix m)	Returns the result of postmultiplying this by m.
RealMatrix	RealMatrix.multiply(RealMatrix m)	Returns the result of postmultiplying this by m.
RealMatrix	ArrayRealVector.outerProduct(RealVector v)	Compute the outer product.
RealMatrix	RealVector.outerProduct(RealVector v)	Compute the outer product.
RealMatrix	RealMatrixFormat.parse(String source)	Parse a string to produce a RealMatrix object.
RealMatrix	RealMatrixFormat.parse(String source, ParsePosition pos)	Parse a string to produce a RealMatrix object.
RealMatrix	AbstractRealMatrix.power(int p)	Returns the result of multiplying this with itself p times.
RealMatrix	RealMatrix.power(int p)	Returns the result of multiplying this with itself p times.
RealMatrix	AbstractRealMatrix.preMultiply(RealMatrix m)	Returns the result of premultiplying this by m.
RealMatrix	RealMatrix.preMultiply(RealMatrix m)	Returns the result of premultiplying this by m.
RealMatrix	AbstractRealMatrix.scalarAdd(double d)	Returns the result of adding d to each entry of this.
RealMatrix	RealMatrix.scalarAdd(double d)	Returns the result of adding d to each entry of this.
RealMatrix	AbstractRealMatrix.scalarMultiply(double d)	Returns the result of multiplying each entry of this by d.
RealMatrix	BlockRealMatrix.scalarMultiply(double d)	Returns the result of multiplying each entry of this by d.
RealMatrix	RealMatrix.scalarMultiply(double d)	Returns the result of multiplying each entry of this by d.
RealMatrix	DecompositionSolver.solve(RealMatrix b)	Solve the linear equation A × X = B for matrices A.
RealMatrix	AbstractRealMatrix.subtract(RealMatrix m)	Returns this minus m.
RealMatrix	RealMatrix.subtract(RealMatrix m)	Returns this minus m.
RealMatrix	AbstractRealMatrix.transpose()	Returns the transpose of this matrix.
RealMatrix	RealMatrix.transpose()	Returns the transpose of this matrix.

Methods in org.apache.commons.math4.legacy.linear with parameters of type RealMatrix

Modifier and Type	Method	Description
RealMatrix	AbstractRealMatrix.add(RealMatrix m)	Returns the sum of this and m.
BlockRealMatrix	BlockRealMatrix.add(RealMatrix m)	Returns the sum of this and m.
RealMatrix	RealMatrix.add(RealMatrix m)	Returns the sum of this and m.
static RealMatrix	MatrixUtils.blockInverse(RealMatrix m, int splitIndex)	Computes the inverse of the given matrix by splitting it into 4 sub-matrices.
static void	MatrixUtils.checkSymmetric(RealMatrix matrix, double eps)	Checks whether a matrix is symmetric.
String	RealMatrixFormat.format(RealMatrix m)	This method calls RealMatrixFormat.format(RealMatrix,StringBuffer,FieldPosition).
StringBuffer	RealMatrixFormat.format(RealMatrix matrix, StringBuffer toAppendTo, FieldPosition pos)	Formats a RealMatrix object to produce a string.
static RealMatrix	MatrixUtils.inverse(RealMatrix matrix)	Computes the inverse of the given matrix.
static RealMatrix	MatrixUtils.inverse(RealMatrix matrix, double threshold)	Computes the inverse of the given matrix.
static boolean	MatrixUtils.isSymmetric(RealMatrix matrix, double eps)	Checks whether a matrix is symmetric.
RealMatrix	AbstractRealMatrix.multiply(RealMatrix m)	Returns the result of postmultiplying this by m.
BlockRealMatrix	BlockRealMatrix.multiply(RealMatrix m)	Returns the result of postmultiplying this by m.
RealMatrix	DiagonalMatrix.multiply(RealMatrix m)	Returns the result of postmultiplying this by m.
RealMatrix	OpenMapRealMatrix.multiply(RealMatrix m)	Returns the result of postmultiplying this by m.
RealMatrix	RealMatrix.multiply(RealMatrix m)	Returns the result of postmultiplying this by m.
RealMatrix	AbstractRealMatrix.preMultiply(RealMatrix m)	Returns the result of premultiplying this by m.
RealMatrix	RealMatrix.preMultiply(RealMatrix m)	Returns the result of premultiplying this by m.
static void	MatrixUtils.serializeRealMatrix(RealMatrix matrix, ObjectOutputStream oos)	Serialize a RealMatrix.
void	AbstractRealMatrix.setColumnMatrix(int column, RealMatrix matrix)	Sets the specified column of this matrix to the entries of the specified column matrix.
void	BlockRealMatrix.setColumnMatrix(int column, RealMatrix matrix)	Sets the specified column of this matrix to the entries of the specified column matrix.
void	RealMatrix.setColumnMatrix(int column, RealMatrix matrix)	Sets the specified column of this matrix to the entries of the specified column matrix.
void	AbstractRealMatrix.setRowMatrix(int row, RealMatrix matrix)	Sets the specified row of this matrix to the entries of the specified row matrix.
void	BlockRealMatrix.setRowMatrix(int row, RealMatrix matrix)	Sets the specified row of this matrix to the entries of the specified row matrix.
void	RealMatrix.setRowMatrix(int row, RealMatrix matrix)	Sets the specified row of this matrix to the entries of the specified row matrix.
RealMatrix	DecompositionSolver.solve(RealMatrix b)	Solve the linear equation A × X = B for matrices A.
static void	MatrixUtils.solveLowerTriangularSystem(RealMatrix rm, RealVector b)	Solve a system of composed of a Lower Triangular Matrix RealMatrix.
static void	MatrixUtils.solveUpperTriangularSystem(RealMatrix rm, RealVector b)	Solver a system composed of an Upper Triangular Matrix RealMatrix.
RealMatrix	AbstractRealMatrix.subtract(RealMatrix m)	Returns this minus m.
BlockRealMatrix	BlockRealMatrix.subtract(RealMatrix m)	Returns this minus m.
OpenMapRealMatrix	OpenMapRealMatrix.subtract(RealMatrix m)	Returns this minus m.
RealMatrix	RealMatrix.subtract(RealMatrix m)	Returns this minus m.

Constructors in org.apache.commons.math4.legacy.linear with parameters of type RealMatrix

Constructor	Description
CholeskyDecomposition(RealMatrix matrix)	Calculates the Cholesky decomposition of the given matrix.
CholeskyDecomposition(RealMatrix matrix, double relativeSymmetryThreshold, double absolutePositivityThreshold)	Calculates the Cholesky decomposition of the given matrix.
EigenDecomposition(RealMatrix matrix)	Calculates the eigen decomposition of the given real matrix.
LUDecomposition(RealMatrix matrix)	Calculates the LU-decomposition of the given matrix.
LUDecomposition(RealMatrix matrix, double singularityThreshold)	Calculates the LU-decomposition of the given matrix.
QRDecomposition(RealMatrix matrix)	Calculates the QR-decomposition of the given matrix.
QRDecomposition(RealMatrix matrix, double threshold)	Calculates the QR-decomposition of the given matrix.
RectangularCholeskyDecomposition(RealMatrix matrix)	Decompose a symmetric positive semidefinite matrix.
RectangularCholeskyDecomposition(RealMatrix matrix, double small)	Decompose a symmetric positive semidefinite matrix.
RRQRDecomposition(RealMatrix matrix)	Calculates the QR-decomposition of the given matrix.
RRQRDecomposition(RealMatrix matrix, double threshold)	Calculates the QR-decomposition of the given matrix.
SingularValueDecomposition(RealMatrix matrix)	Calculates the compact Singular Value Decomposition of the given matrix.

Uses of RealMatrix in org.apache.commons.math4.legacy.ml.clustering

Methods in org.apache.commons.math4.legacy.ml.clustering that return RealMatrix

Modifier and Type	Method	Description
RealMatrix	FuzzyKMeansClusterer.getMembershipMatrix()	Returns the nxk membership matrix, where n is the number of data points and k the number of clusters.

Uses of RealMatrix in org.apache.commons.math4.legacy.optim.nonlinear.scalar

Constructors in org.apache.commons.math4.legacy.optim.nonlinear.scalar with parameters of type RealMatrix

Constructor	Description
LeastSquaresConverter(MultivariateVectorFunction function, double[] observations, RealMatrix scale)	Builds a simple converter for correlated residuals with the specified weights.

Uses of RealMatrix in org.apache.commons.math4.legacy.optim.nonlinear.scalar.noderiv

Methods in org.apache.commons.math4.legacy.optim.nonlinear.scalar.noderiv that return types with arguments of type RealMatrix

Modifier and Type	Method	Description
List<RealMatrix>	CMAESOptimizer.getStatisticsDHistory()
List<RealMatrix>	CMAESOptimizer.getStatisticsMeanHistory()

Uses of RealMatrix in org.apache.commons.math4.legacy.random

Constructors in org.apache.commons.math4.legacy.random with parameters of type RealMatrix

Constructor	Description
CorrelatedVectorFactory(double[] mean, RealMatrix covariance, double small)	Correlated vector factory.
CorrelatedVectorFactory(RealMatrix covariance, double small)	Null mean correlated vector factory.

Uses of RealMatrix in org.apache.commons.math4.legacy.stat.correlation

Methods in org.apache.commons.math4.legacy.stat.correlation that return RealMatrix

Modifier and Type	Method	Description
RealMatrix	KendallsCorrelation.computeCorrelationMatrix(double[][] matrix)	Computes the Kendall's Tau rank correlation matrix for the columns of the input rectangular array.
RealMatrix	KendallsCorrelation.computeCorrelationMatrix(RealMatrix matrix)	Computes the Kendall's Tau rank correlation matrix for the columns of the input matrix.
RealMatrix	PearsonsCorrelation.computeCorrelationMatrix(double[][] data)	Computes the correlation matrix for the columns of the input rectangular array.
RealMatrix	PearsonsCorrelation.computeCorrelationMatrix(RealMatrix matrix)	Computes the correlation matrix for the columns of the input matrix, using PearsonsCorrelation.correlation(double[], double[]).
RealMatrix	SpearmansCorrelation.computeCorrelationMatrix(double[][] matrix)	Computes the Spearman's rank correlation matrix for the columns of the input rectangular array.
RealMatrix	SpearmansCorrelation.computeCorrelationMatrix(RealMatrix matrix)	Computes the Spearman's rank correlation matrix for the columns of the input matrix.
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.
RealMatrix	PearsonsCorrelation.covarianceToCorrelation(RealMatrix covarianceMatrix)	Derives a correlation matrix from a covariance matrix.
RealMatrix	KendallsCorrelation.getCorrelationMatrix()	Returns the correlation matrix.
RealMatrix	PearsonsCorrelation.getCorrelationMatrix()	Returns the correlation matrix.
RealMatrix	SpearmansCorrelation.getCorrelationMatrix()	Calculate the Spearman Rank Correlation Matrix.
RealMatrix	PearsonsCorrelation.getCorrelationPValues()	Returns a matrix of p-values associated with the (two-sided) null hypothesis that the corresponding correlation coefficient is zero.
RealMatrix	PearsonsCorrelation.getCorrelationStandardErrors()	Returns a matrix of standard errors associated with the estimates in the correlation matrix. getCorrelationStandardErrors().getEntry(i,j) is the standard error associated with getCorrelationMatrix.getEntry(i,j)
RealMatrix	Covariance.getCovarianceMatrix()	Returns the covariance matrix.
RealMatrix	StorelessCovariance.getCovarianceMatrix()	Returns the covariance matrix.

Methods in org.apache.commons.math4.legacy.stat.correlation with parameters of type RealMatrix

Modifier and Type	Method	Description
RealMatrix	KendallsCorrelation.computeCorrelationMatrix(RealMatrix matrix)	Computes the Kendall's Tau rank correlation matrix for the columns of the input matrix.
RealMatrix	PearsonsCorrelation.computeCorrelationMatrix(RealMatrix matrix)	Computes the correlation matrix for the columns of the input matrix, using PearsonsCorrelation.correlation(double[], double[]).
RealMatrix	SpearmansCorrelation.computeCorrelationMatrix(RealMatrix matrix)	Computes the Spearman's rank correlation matrix for the columns of the input matrix.
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.
RealMatrix	PearsonsCorrelation.covarianceToCorrelation(RealMatrix covarianceMatrix)	Derives a correlation matrix from a covariance matrix.

Constructors in org.apache.commons.math4.legacy.stat.correlation with parameters of type RealMatrix

Constructor	Description
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.
KendallsCorrelation(RealMatrix matrix)	Create a KendallsCorrelation from a RealMatrix whose columns represent variables to be correlated.
PearsonsCorrelation(RealMatrix matrix)	Create a PearsonsCorrelation from a RealMatrix whose columns represent variables to be correlated.
PearsonsCorrelation(RealMatrix covarianceMatrix, int numberOfObservations)	Create a PearsonsCorrelation from a covariance matrix.
SpearmansCorrelation(RealMatrix dataMatrix)	Create a SpearmansCorrelation from the given data matrix.
SpearmansCorrelation(RealMatrix dataMatrix, RankingAlgorithm rankingAlgorithm)	Create a SpearmansCorrelation with the given input data matrix and ranking algorithm.

Uses of RealMatrix in org.apache.commons.math4.legacy.stat.descriptive

Methods in org.apache.commons.math4.legacy.stat.descriptive that return RealMatrix

Modifier and Type	Method	Description
RealMatrix	MultivariateSummaryStatistics.getCovariance()	Returns the covariance matrix of the values that have been added.
RealMatrix	StatisticalMultivariateSummary.getCovariance()	Returns the covariance of the available values.
RealMatrix	SynchronizedMultivariateSummaryStatistics.getCovariance()	Returns the covariance matrix of the values that have been added.

Uses of RealMatrix in org.apache.commons.math4.legacy.stat.descriptive.moment

Methods in org.apache.commons.math4.legacy.stat.descriptive.moment that return RealMatrix

Modifier and Type	Method	Description
RealMatrix	VectorialCovariance.getResult()	Get the covariance matrix.

Uses of RealMatrix in org.apache.commons.math4.legacy.stat.regression

Methods in org.apache.commons.math4.legacy.stat.regression that return RealMatrix

Modifier and Type	Method	Description
protected abstract RealMatrix	AbstractMultipleLinearRegression.calculateBetaVariance()	Calculates the beta variance of multiple linear regression in matrix notation.
protected RealMatrix	GLSMultipleLinearRegression.calculateBetaVariance()	Calculates the variance on the beta.
protected RealMatrix	OLSMultipleLinearRegression.calculateBetaVariance()	Calculates the variance-covariance matrix of the regression parameters.
RealMatrix	OLSMultipleLinearRegression.calculateHat()	Compute the "hat" matrix.
protected RealMatrix	GLSMultipleLinearRegression.getOmegaInverse()	Get the inverse of the covariance.
protected RealMatrix	AbstractMultipleLinearRegression.getX()