Uses of Interface
org.apache.commons.math3.linear.RealMatrix

Packages that use RealMatrix

Package	Description
org.apache.commons.math3.distribution	Implementations of common discrete and continuous distributions.
org.apache.commons.math3.filter	Implementations of common discrete-time linear filters.
org.apache.commons.math3.fitting.leastsquares	This package provides algorithms that minimize the residuals between observations and model values.
org.apache.commons.math3.linear	Linear algebra support.
org.apache.commons.math3.ml.clustering	Clustering algorithms.
org.apache.commons.math3.ode.nonstiff	This package provides classes to solve non-stiff Ordinary Differential Equations problems.
org.apache.commons.math3.optim.nonlinear.scalar	Algorithms for optimizing a scalar function.
org.apache.commons.math3.optim.nonlinear.scalar.noderiv	This package provides optimization algorithms that do not require derivatives.
org.apache.commons.math3.optim.nonlinear.vector	Algorithms for optimizing a vector function.
org.apache.commons.math3.optim.nonlinear.vector.jacobian	This package provides optimization algorithms that require derivatives.
org.apache.commons.math3.optimization	All classes and sub-packages of this package are deprecated.
org.apache.commons.math3.optimization.direct	This package provides optimization algorithms that don't require derivatives.
org.apache.commons.math3.optimization.general	This package provides optimization algorithms that require derivatives.
org.apache.commons.math3.optimization.linear	This package provides optimization algorithms for linear constrained problems.
org.apache.commons.math3.random	Random number and random data generators.
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.inference	Classes providing hypothesis testing.
org.apache.commons.math3.stat.regression	Statistical routines involving multivariate data.

Uses of RealMatrix in org.apache.commons.math3.distribution

Fields in org.apache.commons.math3.distribution declared as RealMatrix

Modifier and Type	Field	Description
private final RealMatrix	MultivariateNormalDistribution.covarianceMatrix	Covariance matrix.
private final RealMatrix	MultivariateNormalDistribution.covarianceMatrixInverse	The matrix inverse of the covariance matrix.
private final RealMatrix	MultivariateNormalDistribution.samplingMatrix	Matrix used in computation of samples.

Methods in org.apache.commons.math3.distribution that return RealMatrix

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

Uses of RealMatrix in org.apache.commons.math3.filter

Fields in org.apache.commons.math3.filter declared as RealMatrix

Modifier and Type	Field	Description
private RealMatrix	DefaultProcessModel.controlMatrix	The control matrix, used to integrate a control input into the state estimation.
private RealMatrix	KalmanFilter.controlMatrix	The control matrix, equivalent to B.
private RealMatrix	KalmanFilter.errorCovariance	The error covariance matrix, equivalent to P.
private RealMatrix	DefaultProcessModel.initialErrorCovMatrix	The initial error covariance matrix of the observed process.
private RealMatrix	DefaultMeasurementModel.measurementMatrix	The measurement matrix, used to associate the measurement vector to the internal state estimation vector.
private RealMatrix	KalmanFilter.measurementMatrix	The measurement matrix, equivalent to H.
private RealMatrix	KalmanFilter.measurementMatrixT	The transposed measurement matrix.
private RealMatrix	DefaultMeasurementModel.measurementNoise	The measurement noise covariance matrix.
private RealMatrix	DefaultProcessModel.processNoiseCovMatrix	The process noise covariance matrix.
private RealMatrix	DefaultProcessModel.stateTransitionMatrix	The state transition matrix, used to advance the internal state estimation each time-step.
private RealMatrix	KalmanFilter.transitionMatrix	The transition matrix, equivalent to A.
private RealMatrix	KalmanFilter.transitionMatrixT	The transposed transition matrix.

Methods in org.apache.commons.math3.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.math3.filter with parameters of type RealMatrix

Modifier	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.math3.fitting.leastsquares

Fields in org.apache.commons.math3.fitting.leastsquares declared as RealMatrix

Modifier and Type	Field	Description
private final RealMatrix	LeastSquaresFactory.LocalLeastSquaresProblem.UnweightedEvaluation.jacobian	Derivative at point.
private RealMatrix	LeastSquaresBuilder.weight	weight matrix
private final RealMatrix	DenseWeightedEvaluation.weightSqrt	reference to the weight square root matrix

Methods in org.apache.commons.math3.fitting.leastsquares that return RealMatrix

Modifier and Type	Method	Description
RealMatrix	LeastSquaresFactory.LocalValueAndJacobianFunction.computeJacobian(double[] params)	Compute the Jacobian.
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	OptimumImpl.getCovariances(double threshold)	Get the covariance matrix of the optimized parameters.
RealMatrix	DenseWeightedEvaluation.getJacobian()	Get the weighted Jacobian matrix.
RealMatrix	LeastSquaresFactory.LocalLeastSquaresProblem.LazyUnweightedEvaluation.getJacobian()	Get the weighted Jacobian matrix.
RealMatrix	LeastSquaresFactory.LocalLeastSquaresProblem.UnweightedEvaluation.getJacobian()	Get the weighted Jacobian matrix.
RealMatrix	LeastSquaresProblem.Evaluation.getJacobian()	Get the weighted Jacobian matrix.
RealMatrix	OptimumImpl.getJacobian()	Get the weighted Jacobian matrix.
private static RealMatrix	LeastSquaresFactory.squareRoot(RealMatrix m)	Computes the square-root of the weight matrix.

Methods in org.apache.commons.math3.fitting.leastsquares that return types with arguments of type RealMatrix

Modifier and Type	Method	Description
private static Pair<RealMatrix,RealVector>	GaussNewtonOptimizer.computeNormalMatrix(RealMatrix jacobian, RealVector residuals)	Compute the normal matrix, JTJ.
Pair<RealVector,RealMatrix>	LeastSquaresFactory.LocalValueAndJacobianFunction.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.math3.fitting.leastsquares with parameters of type RealMatrix

Modifier and Type	Method	Description
private static Pair<RealMatrix,RealVector>	GaussNewtonOptimizer.computeNormalMatrix(RealMatrix jacobian, RealVector residuals)	Compute the normal matrix, JTJ.
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.
private LevenbergMarquardtOptimizer.InternalData	LevenbergMarquardtOptimizer.qrDecomposition(RealMatrix jacobian, int solvedCols)	Decompose a matrix A as A.P = Q.R using Householder transforms.
protected abstract RealVector	GaussNewtonOptimizer.Decomposition.solve(RealMatrix jacobian, RealVector residuals)	Solve the linear least squares problem Jx=r.
private static RealMatrix	LeastSquaresFactory.squareRoot(RealMatrix m)	Computes the square-root of the weight matrix.
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.

Constructors in org.apache.commons.math3.fitting.leastsquares with parameters of type RealMatrix

Modifier	Constructor	Description
(package private)	DenseWeightedEvaluation(LeastSquaresProblem.Evaluation unweighted, RealMatrix weightSqrt)	Create a weighted evaluation from an unweighted one.
private	UnweightedEvaluation(RealVector values, RealMatrix jacobian, RealVector target, RealVector point)	Create an LeastSquaresProblem.Evaluation with no weights.

Uses of RealMatrix in org.apache.commons.math3.linear

Subinterfaces of RealMatrix in org.apache.commons.math3.linear

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

Classes in org.apache.commons.math3.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.

Fields in org.apache.commons.math3.linear declared as RealMatrix

Modifier and Type	Field	Description
private RealMatrix	BiDiagonalTransformer.cachedB	Cached value of B.
private RealMatrix	EigenDecomposition.cachedD	Cached value of D.
private RealMatrix	HessenbergTransformer.cachedH	Cached value of H.
private RealMatrix	QRDecomposition.cachedH	Cached value of H.
private RealMatrix	CholeskyDecomposition.cachedL	Cached value of L.
private RealMatrix	LUDecomposition.cachedL	Cached value of L.
private RealMatrix	CholeskyDecomposition.cachedLT	Cached value of LT.
private RealMatrix	HessenbergTransformer.cachedP	Cached value of P.
private RealMatrix	LUDecomposition.cachedP	Cached value of P.
private RealMatrix	RRQRDecomposition.cachedP	Cached value of P.
private RealMatrix	SchurTransformer.cachedP	Cached value of P.
private RealMatrix	HessenbergTransformer.cachedPt	Cached value of Pt.
private RealMatrix	SchurTransformer.cachedPt	Cached value of PT.
private RealMatrix	QRDecomposition.cachedQ	Cached value of Q.
private RealMatrix	TriDiagonalTransformer.cachedQ	Cached value of Q.
private RealMatrix	TriDiagonalTransformer.cachedQt	Cached value of Qt.
private RealMatrix	QRDecomposition.cachedQT	Cached value of QT.
private RealMatrix	QRDecomposition.cachedR	Cached value of R.
private RealMatrix	SingularValueDecomposition.cachedS	Cached value of S (diagonal) matrix.
private RealMatrix	SchurTransformer.cachedT	Cached value of T.
private RealMatrix	TriDiagonalTransformer.cachedT	Cached value of T.
private RealMatrix	BiDiagonalTransformer.cachedU	Cached value of U.
private RealMatrix	LUDecomposition.cachedU	Cached value of U.
private final RealMatrix	SingularValueDecomposition.cachedU	Cached value of U matrix.
private RealMatrix	SingularValueDecomposition.cachedUt	Cached value of transposed U matrix.
private RealMatrix	BiDiagonalTransformer.cachedV	Cached value of V.
private RealMatrix	EigenDecomposition.cachedV	Cached value of V.
private final RealMatrix	SingularValueDecomposition.cachedV	Cached value of V matrix.
private RealMatrix	EigenDecomposition.cachedVt	Cached value of Vt.
private RealMatrix	SingularValueDecomposition.cachedVt	Cached value of transposed V matrix.
private RealMatrix	RRQRDecomposition.Solver.p	A permutation matrix for the pivots used in the QR decomposition
private final RealMatrix	SingularValueDecomposition.Solver.pseudoInverse	Pseudo-inverse of the initial matrix.
private final RealMatrix	RectangularCholeskyDecomposition.root	Permutated Cholesky root of the symmetric positive semidefinite matrix.

Methods in org.apache.commons.math3.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.createRealDiagonalMatrix(double[] diagonal)	Returns a diagonal matrix with specified elements.
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 the values in the the input array.
static RealMatrix	MatrixUtils.createRealMatrix(int rows, int columns)	Returns a RealMatrix with specified dimensions.
static RealMatrix	MatrixUtils.createRowRealMatrix(double[] rowData)	Create a row RealMatrix using the data from the input array.
RealMatrix	BiDiagonalTransformer.getB()	Returns the bi-diagonal matrix B of the transform.
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	HessenbergTransformer.getH()	Returns the Hessenberg matrix H of the transform.
RealMatrix	QRDecomposition.getH()	Returns the Householder reflector vectors.
RealMatrix	CholeskyDecomposition.Solver.getInverse()	Get the inverse of the decomposed matrix.
RealMatrix	DecompositionSolver.getInverse()	Get the pseudo-inverse of the decomposed matrix.
RealMatrix	EigenDecomposition.Solver.getInverse()	Get the inverse of the decomposed matrix.
RealMatrix	LUDecomposition.Solver.getInverse()	Get the inverse of the decomposed matrix.
RealMatrix	QRDecomposition.Solver.getInverse()	Get the pseudo-inverse of the decomposed matrix.
RealMatrix	RRQRDecomposition.Solver.getInverse()	Get the pseudo-inverse of the decomposed matrix.
RealMatrix	SingularValueDecomposition.Solver.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	HessenbergTransformer.getP()	Returns the matrix P of the transform.
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	SchurTransformer.getP()	Returns the matrix P of the transform.
RealMatrix	HessenbergTransformer.getPT()	Returns the transpose of the matrix P of the transform.
RealMatrix	SchurTransformer.getPT()	Returns the transpose of the matrix P of the transform.
RealMatrix	QRDecomposition.getQ()	Returns the matrix Q of the decomposition.
RealMatrix	TriDiagonalTransformer.getQ()	Returns the matrix Q of the transform.
RealMatrix	QRDecomposition.getQT()	Returns the transpose of the matrix Q of the decomposition.
RealMatrix	TriDiagonalTransformer.getQT()	Returns the transpose of the matrix Q of the transform.
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	RealMatrix.getSubMatrix(int[] selectedRows, int[] selectedColumns)	Gets a submatrix.
RealMatrix	RealMatrix.getSubMatrix(int startRow, int endRow, int startColumn, int endColumn)	Gets a submatrix.
RealMatrix	SchurTransformer.getT()	Returns the quasi-triangular Schur matrix T of the transform.
RealMatrix	TriDiagonalTransformer.getT()	Returns the tridiagonal matrix T of the transform.
RealMatrix	BiDiagonalTransformer.getU()	Returns the matrix U of the transform.
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	BiDiagonalTransformer.getV()	Returns the matrix V of the transform.
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	CholeskyDecomposition.Solver.solve(RealMatrix b)	Solve the linear equation A × X = B for matrices A.
RealMatrix	DecompositionSolver.solve(RealMatrix b)	Solve the linear equation A × X = B for matrices A.
RealMatrix	EigenDecomposition.Solver.solve(RealMatrix b)	Solve the linear equation A × X = B for matrices A.
RealMatrix	LUDecomposition.Solver.solve(RealMatrix b)	Solve the linear equation A × X = B for matrices A.
RealMatrix	QRDecomposition.Solver.solve(RealMatrix b)	Solve the linear equation A × X = B for matrices A.
RealMatrix	RRQRDecomposition.Solver.solve(RealMatrix b)	Solve the linear equation A × X = B for matrices A.
RealMatrix	SingularValueDecomposition.Solver.solve(RealMatrix b)	Solve the linear equation A × X = B in least square sense.
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.math3.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.
private static boolean	MatrixUtils.isSymmetricInternal(RealMatrix matrix, double relativeTolerance, boolean raiseException)	Checks whether a matrix is symmetric, within a given relative tolerance.
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	CholeskyDecomposition.Solver.solve(RealMatrix b)	Solve the linear equation A × X = B for matrices A.
RealMatrix	DecompositionSolver.solve(RealMatrix b)	Solve the linear equation A × X = B for matrices A.
RealMatrix	EigenDecomposition.Solver.solve(RealMatrix b)	Solve the linear equation A × X = B for matrices A.
RealMatrix	LUDecomposition.Solver.solve(RealMatrix b)	Solve the linear equation A × X = B for matrices A.
RealMatrix	QRDecomposition.Solver.solve(RealMatrix b)	Solve the linear equation A × X = B for matrices A.
RealMatrix	RRQRDecomposition.Solver.solve(RealMatrix b)	Solve the linear equation A × X = B for matrices A.
RealMatrix	SingularValueDecomposition.Solver.solve(RealMatrix b)	Solve the linear equation A × X = B in least square sense.
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.
private SchurTransformer	EigenDecomposition.transformToSchur(RealMatrix matrix)	Transforms the matrix to Schur form and calculates the eigenvalues.
private void	EigenDecomposition.transformToTridiagonal(RealMatrix matrix)	Transforms the matrix to tridiagonal form.

Constructors in org.apache.commons.math3.linear with parameters of type RealMatrix

Modifier	Constructor	Description
(package private)	BiDiagonalTransformer(RealMatrix matrix)	Build the transformation to bi-diagonal shape of a matrix.
	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.
	EigenDecomposition(RealMatrix matrix, double splitTolerance)	Deprecated. in 3.1 (to be removed in 4.0) due to unused parameter
(package private)	HessenbergTransformer(RealMatrix matrix)	Build the transformation to Hessenberg form of a general 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.
(package private)	SchurTransformer(RealMatrix matrix)	Build the transformation to Schur form of a general real matrix.
	SingularValueDecomposition(RealMatrix matrix)	Calculates the compact Singular Value Decomposition of the given matrix.
private	Solver(DecompositionSolver upper, RealMatrix p)	Build a solver from decomposed matrix.
private	Solver(double[] singularValues, RealMatrix uT, RealMatrix v, boolean nonSingular, double tol)	Build a solver from decomposed matrix.
(package private)	TriDiagonalTransformer(RealMatrix matrix)	Build the transformation to tridiagonal shape of a symmetrical matrix.

Uses of RealMatrix in org.apache.commons.math3.ml.clustering

Methods in org.apache.commons.math3.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.math3.ode.nonstiff

Methods in org.apache.commons.math3.ode.nonstiff with parameters of type RealMatrix

Modifier and Type	Method	Description
private double	AdamsBashforthIntegrator.errorEstimation(double[] previousState, double[] predictedState, double[] predictedScaled, RealMatrix predictedNordsieck)	Estimate error.

Uses of RealMatrix in org.apache.commons.math3.optim.nonlinear.scalar

Fields in org.apache.commons.math3.optim.nonlinear.scalar declared as RealMatrix

Modifier and Type	Field	Description
private final RealMatrix	LeastSquaresConverter.scale	Optional scaling matrix (weight and correlations) for the residuals.

Constructors in org.apache.commons.math3.optim.nonlinear.scalar with parameters of type RealMatrix

Modifier	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.math3.optim.nonlinear.scalar.noderiv

Fields in org.apache.commons.math3.optim.nonlinear.scalar.noderiv declared as RealMatrix

Modifier and Type	Field	Description
private RealMatrix	CMAESOptimizer.B	Coordinate system.
private RealMatrix	CMAESOptimizer.BD	B*D, stored for efficiency.
private RealMatrix	CMAESOptimizer.C	Covariance matrix.
private RealMatrix	CMAESOptimizer.D	Scaling.
private RealMatrix	CMAESOptimizer.diagC	Diagonal of C, used for diagonalOnly.
private RealMatrix	CMAESOptimizer.diagD	Diagonal of sqrt(D), stored for efficiency.
private RealMatrix	CMAESOptimizer.pc	Evolution path.
private RealMatrix	CMAESOptimizer.ps	Evolution path for sigma.
private RealMatrix	CMAESOptimizer.weights	Array for weighted recombination.
private RealMatrix	CMAESOptimizer.xmean	Objective variables.

Fields in org.apache.commons.math3.optim.nonlinear.scalar.noderiv with type parameters of type RealMatrix

Modifier and Type	Field	Description
private final List<RealMatrix>	CMAESOptimizer.statisticsDHistory	History of D matrix.
private final List<RealMatrix>	CMAESOptimizer.statisticsMeanHistory	History of mean matrix.

Methods in org.apache.commons.math3.optim.nonlinear.scalar.noderiv that return RealMatrix

Modifier and Type	Method	Description
private static RealMatrix	CMAESOptimizer.diag(RealMatrix m)
private static RealMatrix	CMAESOptimizer.divide(RealMatrix m, RealMatrix n)
private static RealMatrix	CMAESOptimizer.eye(int n, int m)
private static RealMatrix	CMAESOptimizer.log(RealMatrix m)
private static RealMatrix	CMAESOptimizer.ones(int n, int m)
private RealMatrix	CMAESOptimizer.randn1(int size, int popSize)
private static RealMatrix	CMAESOptimizer.repmat(RealMatrix mat, int n, int m)
private static RealMatrix	CMAESOptimizer.selectColumns(RealMatrix m, int[] cols)
private static RealMatrix	CMAESOptimizer.sequence(double start, double end, double step)
private static RealMatrix	CMAESOptimizer.sqrt(RealMatrix m)
private static RealMatrix	CMAESOptimizer.square(RealMatrix m)
private static RealMatrix	CMAESOptimizer.sumRows(RealMatrix m)
private static RealMatrix	CMAESOptimizer.times(RealMatrix m, RealMatrix n)
private static RealMatrix	CMAESOptimizer.triu(RealMatrix m, int k)
private static RealMatrix	CMAESOptimizer.zeros(int n, int m)

Methods in org.apache.commons.math3.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()

Methods in org.apache.commons.math3.optim.nonlinear.scalar.noderiv with parameters of type RealMatrix

Modifier and Type	Method	Description
private static void	CMAESOptimizer.copyColumn(RealMatrix m1, int col1, RealMatrix m2, int col2)	Copies a column from m1 to m2.
private static RealMatrix	CMAESOptimizer.diag(RealMatrix m)
private static RealMatrix	CMAESOptimizer.divide(RealMatrix m, RealMatrix n)
private static RealMatrix	CMAESOptimizer.log(RealMatrix m)
private static double	CMAESOptimizer.max(RealMatrix m)
private static double	CMAESOptimizer.min(RealMatrix m)
private static RealMatrix	CMAESOptimizer.repmat(RealMatrix mat, int n, int m)
private static RealMatrix	CMAESOptimizer.selectColumns(RealMatrix m, int[] cols)
private static RealMatrix	CMAESOptimizer.sqrt(RealMatrix m)
private static RealMatrix	CMAESOptimizer.square(RealMatrix m)
private static RealMatrix	CMAESOptimizer.sumRows(RealMatrix m)
private static RealMatrix	CMAESOptimizer.times(RealMatrix m, RealMatrix n)
private static RealMatrix	CMAESOptimizer.triu(RealMatrix m, int k)
private void	CMAESOptimizer.updateCovariance(boolean hsig, RealMatrix bestArx, RealMatrix arz, int[] arindex, RealMatrix xold)	Update of the covariance matrix C.
private void	CMAESOptimizer.updateCovarianceDiagonalOnly(boolean hsig, RealMatrix bestArz)	Update of the covariance matrix C for diagonalOnly > 0
private boolean	CMAESOptimizer.updateEvolutionPaths(RealMatrix zmean, RealMatrix xold)	Update of the evolution paths ps and pc.

Uses of RealMatrix in org.apache.commons.math3.optim.nonlinear.vector

Fields in org.apache.commons.math3.optim.nonlinear.vector declared as RealMatrix

Modifier and Type	Field	Description
private RealMatrix	MultivariateVectorOptimizer.weightMatrix	Deprecated. Weight matrix.
private final RealMatrix	Weight.weightMatrix	Deprecated. Weight matrix.

Methods in org.apache.commons.math3.optim.nonlinear.vector that return RealMatrix

Modifier and Type	Method	Description
RealMatrix	MultivariateVectorOptimizer.getWeight()	Deprecated. Gets the weight matrix of the observations.
RealMatrix	Weight.getWeight()	Deprecated. Gets the initial guess.

Constructors in org.apache.commons.math3.optim.nonlinear.vector with parameters of type RealMatrix

Modifier	Constructor	Description
	Weight(RealMatrix weight)	Deprecated.

Uses of RealMatrix in org.apache.commons.math3.optim.nonlinear.vector.jacobian

Fields in org.apache.commons.math3.optim.nonlinear.vector.jacobian declared as RealMatrix

Modifier and Type	Field	Description
private RealMatrix	AbstractLeastSquaresOptimizer.weightMatrixSqrt	Deprecated. Square-root of the weight matrix.

Methods in org.apache.commons.math3.optim.nonlinear.vector.jacobian that return RealMatrix

Modifier and Type	Method	Description
protected RealMatrix	AbstractLeastSquaresOptimizer.computeWeightedJacobian(double[] params)	Deprecated. Computes the weighted Jacobian matrix.
RealMatrix	AbstractLeastSquaresOptimizer.getWeightSquareRoot()	Deprecated. Gets the square-root of the weight matrix.
private RealMatrix	AbstractLeastSquaresOptimizer.squareRoot(RealMatrix m)	Deprecated. Computes the square-root of the weight matrix.

Methods in org.apache.commons.math3.optim.nonlinear.vector.jacobian with parameters of type RealMatrix

Modifier and Type	Method	Description
private void	LevenbergMarquardtOptimizer.qrDecomposition(RealMatrix jacobian)	Deprecated. Decompose a matrix A as A.P = Q.R using Householder transforms.
private RealMatrix	AbstractLeastSquaresOptimizer.squareRoot(RealMatrix m)	Deprecated. Computes the square-root of the weight matrix.

Uses of RealMatrix in org.apache.commons.math3.optimization

Fields in org.apache.commons.math3.optimization declared as RealMatrix

Modifier and Type	Field	Description
private final RealMatrix	LeastSquaresConverter.scale	Deprecated. Optional scaling matrix (weight and correlations) for the residuals.
private final RealMatrix	Weight.weightMatrix	Deprecated. Weight matrix.

Methods in org.apache.commons.math3.optimization that return RealMatrix

Modifier and Type	Method	Description
RealMatrix	Weight.getWeight()	Deprecated. Gets the initial guess.

Constructors in org.apache.commons.math3.optimization with parameters of type RealMatrix

Modifier	Constructor	Description
	LeastSquaresConverter(MultivariateVectorFunction function, double[] observations, RealMatrix scale)	Deprecated. Build a simple converter for correlated residuals with the specific weights.
	Weight(RealMatrix weight)	Deprecated.

Uses of RealMatrix in org.apache.commons.math3.optimization.direct

Fields in org.apache.commons.math3.optimization.direct declared as RealMatrix

Modifier and Type	Field	Description
private RealMatrix	CMAESOptimizer.B	Deprecated. Coordinate system.
private RealMatrix	CMAESOptimizer.BD	Deprecated. B*D, stored for efficiency.
private RealMatrix	CMAESOptimizer.C	Deprecated. Covariance matrix.
private RealMatrix	CMAESOptimizer.D	Deprecated. Scaling.
private RealMatrix	CMAESOptimizer.diagC	Deprecated. Diagonal of C, used for diagonalOnly.
private RealMatrix	CMAESOptimizer.diagD	Deprecated. Diagonal of sqrt(D), stored for efficiency.
private RealMatrix	CMAESOptimizer.pc	Deprecated. Evolution path.
private RealMatrix	CMAESOptimizer.ps	Deprecated. Evolution path for sigma.
private RealMatrix	BaseAbstractMultivariateVectorOptimizer.weightMatrix	Deprecated. Weight matrix.
private RealMatrix	CMAESOptimizer.weights	Deprecated. Array for weighted recombination.
private RealMatrix	CMAESOptimizer.xmean	Deprecated. Objective variables.

Fields in org.apache.commons.math3.optimization.direct with type parameters of type RealMatrix

Modifier and Type	Field	Description
private List<RealMatrix>	CMAESOptimizer.statisticsDHistory	Deprecated. History of D matrix.
private List<RealMatrix>	CMAESOptimizer.statisticsMeanHistory	Deprecated. History of mean matrix.

Methods in org.apache.commons.math3.optimization.direct that return RealMatrix

Modifier and Type	Method	Description
private static RealMatrix	CMAESOptimizer.diag(RealMatrix m)	Deprecated.
private static RealMatrix	CMAESOptimizer.divide(RealMatrix m, RealMatrix n)	Deprecated.
private static RealMatrix	CMAESOptimizer.eye(int n, int m)	Deprecated.
RealMatrix	BaseAbstractMultivariateVectorOptimizer.getWeight()	Deprecated. Gets the weight matrix of the observations.
private static RealMatrix	CMAESOptimizer.log(RealMatrix m)	Deprecated.
private static RealMatrix	CMAESOptimizer.ones(int n, int m)	Deprecated.
private RealMatrix	CMAESOptimizer.randn1(int size, int popSize)	Deprecated.
private static RealMatrix	CMAESOptimizer.repmat(RealMatrix mat, int n, int m)	Deprecated.
private static RealMatrix	CMAESOptimizer.selectColumns(RealMatrix m, int[] cols)	Deprecated.
private static RealMatrix	CMAESOptimizer.sequence(double start, double end, double step)	Deprecated.
private static RealMatrix	CMAESOptimizer.sqrt(RealMatrix m)	Deprecated.
private static RealMatrix	CMAESOptimizer.square(RealMatrix m)	Deprecated.
private static RealMatrix	CMAESOptimizer.sumRows(RealMatrix m)	Deprecated.
private static RealMatrix	CMAESOptimizer.times(RealMatrix m, RealMatrix n)	Deprecated.
private static RealMatrix	CMAESOptimizer.triu(RealMatrix m, int k)	Deprecated.
private static RealMatrix	CMAESOptimizer.zeros(int n, int m)	Deprecated.

Methods in org.apache.commons.math3.optimization.direct that return types with arguments of type RealMatrix

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

Methods in org.apache.commons.math3.optimization.direct with parameters of type RealMatrix

Modifier and Type	Method	Description
private static void	CMAESOptimizer.copyColumn(RealMatrix m1, int col1, RealMatrix m2, int col2)	Deprecated. Copies a column from m1 to m2.
private static RealMatrix	CMAESOptimizer.diag(RealMatrix m)	Deprecated.
private static RealMatrix	CMAESOptimizer.divide(RealMatrix m, RealMatrix n)	Deprecated.
private static RealMatrix	CMAESOptimizer.log(RealMatrix m)	Deprecated.
private static double	CMAESOptimizer.max(RealMatrix m)	Deprecated.
private static double	CMAESOptimizer.min(RealMatrix m)	Deprecated.
private static RealMatrix	CMAESOptimizer.repmat(RealMatrix mat, int n, int m)	Deprecated.
private static RealMatrix	CMAESOptimizer.selectColumns(RealMatrix m, int[] cols)	Deprecated.
private static RealMatrix	CMAESOptimizer.sqrt(RealMatrix m)	Deprecated.
private static RealMatrix	CMAESOptimizer.square(RealMatrix m)	Deprecated.
private static RealMatrix	CMAESOptimizer.sumRows(RealMatrix m)	Deprecated.
private static RealMatrix	CMAESOptimizer.times(RealMatrix m, RealMatrix n)	Deprecated.
private static RealMatrix	CMAESOptimizer.triu(RealMatrix m, int k)	Deprecated.
private void	CMAESOptimizer.updateCovariance(boolean hsig, RealMatrix bestArx, RealMatrix arz, int[] arindex, RealMatrix xold)	Deprecated. Update of the covariance matrix C.
private void	CMAESOptimizer.updateCovarianceDiagonalOnly(boolean hsig, RealMatrix bestArz)	Deprecated. Update of the covariance matrix C for diagonalOnly > 0
private boolean	CMAESOptimizer.updateEvolutionPaths(RealMatrix zmean, RealMatrix xold)	Deprecated. Update of the evolution paths ps and pc.

Uses of RealMatrix in org.apache.commons.math3.optimization.general

Fields in org.apache.commons.math3.optimization.general declared as RealMatrix

Modifier and Type	Field	Description
private RealMatrix	AbstractLeastSquaresOptimizer.weightMatrixSqrt	Deprecated. Square-root of the weight matrix.

Methods in org.apache.commons.math3.optimization.general that return RealMatrix

Modifier and Type	Method	Description
protected RealMatrix	AbstractLeastSquaresOptimizer.computeWeightedJacobian(double[] params)	Deprecated. Computes the Jacobian matrix.
RealMatrix	AbstractLeastSquaresOptimizer.getWeightSquareRoot()	Deprecated. Gets the square-root of the weight matrix.
private RealMatrix	AbstractLeastSquaresOptimizer.squareRoot(RealMatrix m)	Deprecated. Computes the square-root of the weight matrix.

Methods in org.apache.commons.math3.optimization.general with parameters of type RealMatrix

Modifier and Type	Method	Description
private void	LevenbergMarquardtOptimizer.qrDecomposition(RealMatrix jacobian)	Deprecated. Decompose a matrix A as A.P = Q.R using Householder transforms.
private RealMatrix	AbstractLeastSquaresOptimizer.squareRoot(RealMatrix m)	Deprecated. Computes the square-root of the weight matrix.

Uses of RealMatrix in org.apache.commons.math3.optimization.linear

Fields in org.apache.commons.math3.optimization.linear declared as RealMatrix

Modifier and Type	Field	Description
private RealMatrix	SimplexTableau.tableau	Deprecated. Simple tableau.

Methods in org.apache.commons.math3.optimization.linear that return RealMatrix

Modifier and Type	Method	Description
protected RealMatrix	SimplexTableau.createTableau(boolean maximize)	Deprecated. Create the tableau by itself.

Uses of RealMatrix in org.apache.commons.math3.random

Fields in org.apache.commons.math3.random declared as RealMatrix

Modifier and Type	Field	Description
private final RealMatrix	CorrelatedRandomVectorGenerator.root	Root of the covariance matrix.

Methods in org.apache.commons.math3.random that return RealMatrix

Modifier and Type	Method	Description
RealMatrix	CorrelatedRandomVectorGenerator.getRootMatrix()	Get the root of the covariance matrix.

Constructors in org.apache.commons.math3.random with parameters of type RealMatrix

Modifier	Constructor	Description
	CorrelatedRandomVectorGenerator(double[] mean, RealMatrix covariance, double small, NormalizedRandomGenerator generator)	Builds a correlated random vector generator from its mean vector and covariance matrix.
	CorrelatedRandomVectorGenerator(RealMatrix covariance, double small, NormalizedRandomGenerator generator)	Builds a null mean random correlated vector generator from its covariance matrix.

Uses of RealMatrix in org.apache.commons.math3.stat.correlation

Fields in org.apache.commons.math3.stat.correlation declared as RealMatrix

Modifier and Type	Field	Description
private final RealMatrix	KendallsCorrelation.correlationMatrix	correlation matrix
private final RealMatrix	PearsonsCorrelation.correlationMatrix	correlation matrix
private final RealMatrix	Covariance.covarianceMatrix	covariance matrix
private final RealMatrix	SpearmansCorrelation.data	Input data

Methods in org.apache.commons.math3.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
private RealMatrix	SpearmansCorrelation.rankTransform(RealMatrix matrix)	Applies rank transform to each of the columns of matrix using the current rankingAlgorithm.

Methods in org.apache.commons.math3.stat.correlation with parameters of type RealMatrix

Modifier and Type	Method	Description
private void	Covariance.checkSufficientData(RealMatrix matrix)	Throws MathIllegalArgumentException if the matrix does not have at least one column and two rows.
private void	PearsonsCorrelation.checkSufficientData(RealMatrix matrix)	Throws MathIllegalArgumentException if the matrix does not have at least two columns and two rows.
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.
private RealMatrix	SpearmansCorrelation.rankTransform(RealMatrix matrix)	Applies rank transform to each of the columns of matrix using the current rankingAlgorithm.

Constructors in org.apache.commons.math3.stat.correlation with parameters of type RealMatrix

Modifier	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.math3.stat.descriptive

Methods in org.apache.commons.math3.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.math3.stat.descriptive.moment

Methods in org.apache.commons.math3.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.math3.stat.inference

Methods in org.apache.commons.math3.stat.inference that return RealMatrix

Modifier and Type	Method	Description
private RealMatrix	KolmogorovSmirnovTest.createRoundedH(double d, int n)	Creates H of size m x m as described in [1] (see above) using double-precision.

Uses of RealMatrix in org.apache.commons.math3.stat.regression

Fields in org.apache.commons.math3.stat.regression declared as RealMatrix

Modifier and Type	Field	Description
private RealMatrix	GLSMultipleLinearRegression.Omega	Covariance matrix.
private RealMatrix	GLSMultipleLinearRegression.OmegaInverse	Inverse of covariance matrix.
private RealMatrix	AbstractMultipleLinearRegression.xMatrix	X sample data.

Methods in org.apache.commons.math3.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()