Uses of Interface org.hipparchus.linear.RealMatrix (Hipparchus 1.4 API)

Packages that use RealMatrix
Package	Description
org.hipparchus.clustering	Clustering algorithms.
org.hipparchus.distribution.multivariate	Implementations of multivariate distributions.
org.hipparchus.filtering.kalman	Kalman filter.
org.hipparchus.filtering.kalman.extended	Kalman filter implementation for non-linear processes.
org.hipparchus.filtering.kalman.linear	Kalman filter implementation for linear processes.
org.hipparchus.linear	Linear algebra support.
org.hipparchus.optim.nonlinear.scalar	Algorithms for optimizing a scalar function.
org.hipparchus.optim.nonlinear.scalar.noderiv	This package provides optimization algorithms that do not require derivatives.
org.hipparchus.optim.nonlinear.vector.leastsquares	This package provides algorithms that minimize the residuals between observations and model values.
org.hipparchus.random	Random number and random data generators.
org.hipparchus.stat.correlation	Correlations/Covariance computations.
org.hipparchus.stat.descriptive	Generic univariate and multivariate summary statistic objects.
org.hipparchus.stat.descriptive.vector	Multivariate statistics.
org.hipparchus.stat.regression	Statistical routines involving multivariate data.

Uses of RealMatrix in org.hipparchus.clustering

Methods in org.hipparchus.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.hipparchus.distribution.multivariate

Methods in org.hipparchus.distribution.multivariate that return RealMatrix
Modifier and Type	Method	Description
`RealMatrix`	MultivariateNormalDistribution.`getCovariances()`	Gets the covariance matrix.

Uses of RealMatrix in org.hipparchus.filtering.kalman

Methods in org.hipparchus.filtering.kalman that return RealMatrix
Modifier and Type	Method	Description
`protected RealMatrix`	AbstractKalmanFilter.`computeInnovationCovarianceMatrix(RealMatrix r, RealMatrix h)`	Compute innovation covariance matrix.
`RealMatrix`	Measurement.`getCovariance()`	Get the measurement covariance.
`RealMatrix`	ProcessEstimate.`getCovariance()`	Get the state covariance.
`RealMatrix`	ProcessEstimate.`getInnovationCovariance()`	Get the innovation covariance matrix.
`RealMatrix`	ProcessEstimate.`getKalmanGain()`	Get the Kalman gain matrix.
`RealMatrix`	ProcessEstimate.`getMeasurementJacobian()`	Get the Jacobian of the measurement with respect to the state (H matrix).
`RealMatrix`	ProcessEstimate.`getStateTransitionMatrix()`	Get state transition matrix between previous state and estimated (but not yet corrected) state.

Methods in org.hipparchus.filtering.kalman with parameters of type RealMatrix
Modifier and Type	Method	Description
`protected RealMatrix`	AbstractKalmanFilter.`computeInnovationCovarianceMatrix(RealMatrix r, RealMatrix h)`	Compute innovation covariance matrix.
`protected void`	AbstractKalmanFilter.`correct(T measurement, RealMatrix stm, RealVector innovation, RealMatrix h, RealMatrix s)`	Perform correction step.
`protected void`	AbstractKalmanFilter.`predict(double time, RealVector predictedState, RealMatrix stm, RealMatrix noise)`	Perform prediction step.

Constructors in org.hipparchus.filtering.kalman with parameters of type RealMatrix
Constructor	Description
`ProcessEstimate(double time, RealVector state, RealMatrix covariance)`	Simple constructor.
`ProcessEstimate(double time, RealVector state, RealMatrix covariance, RealMatrix stateTransitionMatrix, RealMatrix measurementJacobian, RealMatrix innovationCovariance, RealMatrix kalmanGain)`	Simple constructor.

Uses of RealMatrix in org.hipparchus.filtering.kalman.extended

Methods in org.hipparchus.filtering.kalman.extended that return RealMatrix
Modifier and Type	Method	Description
`RealMatrix`	NonLinearEvolution.`getMeasurementJacobian()`	Get measurement Jacobian.
`RealMatrix`	NonLinearEvolution.`getProcessNoiseMatrix()`	Get process noise.
`RealMatrix`	NonLinearEvolution.`getStateTransitionMatrix()`	Get state transition matrix between previous and current state.

Methods in org.hipparchus.filtering.kalman.extended with parameters of type RealMatrix
Modifier and Type	Method	Description
`RealVector`	NonLinearProcess.`getInnovation(T measurement, NonLinearEvolution evolution, RealMatrix innovationCovarianceMatrix)`	Get the innovation brought by a measurement.

Constructors in org.hipparchus.filtering.kalman.extended with parameters of type RealMatrix
Constructor	Description
`NonLinearEvolution(double currentTime, RealVector currentState, RealMatrix stateTransitionMatrix, RealMatrix processNoiseMatrix, RealMatrix measurementJacobian)`	Simple constructor.

Uses of RealMatrix in org.hipparchus.filtering.kalman.linear

Methods in org.hipparchus.filtering.kalman.linear that return RealMatrix
Modifier and Type	Method	Description
`RealMatrix`	LinearEvolution.`getControlMatrix()`	Get the control matrix B_k-1.
`RealMatrix`	LinearEvolution.`getMeasurementJacobian()`	Get measurement Jacobian.
`RealMatrix`	LinearEvolution.`getProcessNoiseMatrix()`	Get the process noise matrix Q_k-1.
`RealMatrix`	LinearEvolution.`getStateTransitionMatrix()`	Get the state transition matrix A_k-1.

Constructors in org.hipparchus.filtering.kalman.linear with parameters of type RealMatrix
Constructor	Description
`LinearEvolution(RealMatrix stateTransitionMatrix, RealMatrix controlMatrix, RealVector command, RealMatrix processNoiseMatrix, RealMatrix measurementJacobian)`	Simple constructor.

Uses of RealMatrix in org.hipparchus.linear

Subinterfaces of RealMatrix in org.hipparchus.linear
Modifier and Type	Interface	Description
`interface`	`SparseRealMatrix`	Marker interface for `RealMatrix` implementations that require sparse backing storage

Classes in org.hipparchus.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.hipparchus.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`	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`	RiccatiEquationSolver.`getK()`	Get the linear controller k.
`RealMatrix`	RiccatiEquationSolverImpl.`getK()`	{inheritDoc}
`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`	RiccatiEquationSolver.`getP()`	Get the solution.
`RealMatrix`	RiccatiEquationSolverImpl.`getP()`	{inheritDoc}
`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`	OrderedEigenDecomposition.`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`	Array2DRowRealMatrix.`kroneckerProduct(RealMatrix b)`	Kronecker product of the current matrix and the parameter 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`	Array2DRowRealMatrix.`multiplyTransposed(Array2DRowRealMatrix m)`	Returns the result of postmultiplying `this` by `m^T`.
`RealMatrix`	Array2DRowRealMatrix.`multiplyTransposed(RealMatrix m)`	Returns the result of postmultiplying `this` by `m^T`.
`RealMatrix`	DiagonalMatrix.`multiplyTransposed(RealMatrix m)`	Returns the result of postmultiplying `this` by `m^T`.
`RealMatrix`	OpenMapRealMatrix.`multiplyTransposed(RealMatrix m)`	Returns the result of postmultiplying `this` by `m^T`.
`default RealMatrix`	RealMatrix.`multiplyTransposed(RealMatrix m)`	Returns the result of postmultiplying `this` by `m^T`.
`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`	Array2DRowRealMatrix.`stack()`	Transforms a matrix in a vector (Vectorization).
`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.
`RealMatrix`	Array2DRowRealMatrix.`transposeMultiply(Array2DRowRealMatrix m)`	Returns the result of postmultiplying `this^T` by `m`.
`RealMatrix`	Array2DRowRealMatrix.`transposeMultiply(RealMatrix m)`	Returns the result of postmultiplying `this^T` by `m`.
`RealMatrix`	DiagonalMatrix.`transposeMultiply(RealMatrix m)`	Returns the result of postmultiplying `this^T` by `m`.
`RealMatrix`	OpenMapRealMatrix.`transposeMultiply(RealMatrix m)`	Returns the result of postmultiplying `this^T` by `m`.
`default RealMatrix`	RealMatrix.`transposeMultiply(RealMatrix m)`	Returns the result of postmultiplying `this^T` by `m`.
`RealMatrix`	Array2DRowRealMatrix.`unstackSquare()`	Transforms a one-column stacked matrix into a squared matrix (devectorization).

Methods in org.hipparchus.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.
`protected void`	ComplexEigenDecomposition.`checkDefinition(RealMatrix matrix)`	Check definition of the decomposition in runtime.
`static void`	MatrixUtils.`checkSymmetric(RealMatrix matrix, double eps)`	Checks whether a matrix is symmetric.
`DecompositionSolver`	CholeskyDecomposer.`decompose(RealMatrix a)`	Get a solver for finding the A × X = B solution in least square sense.
`DecompositionSolver`	LUDecomposer.`decompose(RealMatrix a)`	Get a solver for finding the A × X = B solution in least square sense.
`DecompositionSolver`	MatrixDecomposer.`decompose(RealMatrix a)`	Get a solver for finding the A × X = B solution in least square sense.
`DecompositionSolver`	QRDecomposer.`decompose(RealMatrix a)`	Get a solver for finding the A × X = B solution in least square sense.
`DecompositionSolver`	SingularValueDecomposer.`decompose(RealMatrix a)`	Get a solver for finding the A × X = B solution in least square sense.
`protected void`	ComplexEigenDecomposition.`findEigenValues(RealMatrix matrix)`	Compute eigen values using the Schur transform.
`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`	Array2DRowRealMatrix.`kroneckerProduct(RealMatrix b)`	Kronecker product of the current matrix and the parameter matrix.
`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`	Array2DRowRealMatrix.`multiplyTransposed(RealMatrix m)`	Returns the result of postmultiplying `this` by `m^T`.
`BlockRealMatrix`	BlockRealMatrix.`multiplyTransposed(RealMatrix m)`	Returns the result of postmultiplying `this` by `m^T`.
`RealMatrix`	DiagonalMatrix.`multiplyTransposed(RealMatrix m)`	Returns the result of postmultiplying `this` by `m^T`.
`RealMatrix`	OpenMapRealMatrix.`multiplyTransposed(RealMatrix m)`	Returns the result of postmultiplying `this` by `m^T`.
`default RealMatrix`	RealMatrix.`multiplyTransposed(RealMatrix m)`	Returns the result of postmultiplying `this` by `m^T`.
`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`.
`RealMatrix`	Array2DRowRealMatrix.`transposeMultiply(RealMatrix m)`	Returns the result of postmultiplying `this^T` by `m`.
`BlockRealMatrix`	BlockRealMatrix.`transposeMultiply(RealMatrix m)`	Returns the result of postmultiplying `this^T` by `m`.
`RealMatrix`	DiagonalMatrix.`transposeMultiply(RealMatrix m)`	Returns the result of postmultiplying `this^T` by `m`.
`RealMatrix`	OpenMapRealMatrix.`transposeMultiply(RealMatrix m)`	Returns the result of postmultiplying `this^T` by `m`.
`default RealMatrix`	RealMatrix.`transposeMultiply(RealMatrix m)`	Returns the result of postmultiplying `this^T` by `m`.

Constructors in org.hipparchus.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.
`ComplexEigenDecomposition(RealMatrix matrix)`	Constructor for decomposition.
`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.
`OrderedComplexEigenDecomposition(RealMatrix matrix)`	Constructor for the decomposition.
`OrderedEigenDecomposition(RealMatrix matrix)`	Constructor using the EigenDecomposition as starting point for ordering.
`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.
`RiccatiEquationSolverImpl(RealMatrix A, RealMatrix B, RealMatrix Q, RealMatrix R)`	Constructor of the solver.
`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.hipparchus.optim.nonlinear.scalar

Constructors in org.hipparchus.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.hipparchus.optim.nonlinear.scalar.noderiv

Methods in org.hipparchus.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.hipparchus.optim.nonlinear.vector.leastsquares

Methods in org.hipparchus.optim.nonlinear.vector.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.hipparchus.optim.nonlinear.vector.leastsquares that return types with arguments of type RealMatrix
Modifier and Type	Method	Description
`Pair<RealVector,RealMatrix>`	MultivariateJacobianFunction.`value(RealVector point)`	Compute the function value and its Jacobian.

Methods in org.hipparchus.optim.nonlinear.vector.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)`	Deprecated. 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.hipparchus.random

Methods in org.hipparchus.random that return RealMatrix
Modifier and Type	Method	Description
`RealMatrix`	CorrelatedRandomVectorGenerator.`getRootMatrix()`	Get the root of the covariance matrix.

Constructors in org.hipparchus.random with parameters of type RealMatrix
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.hipparchus.stat.correlation

Methods in org.hipparchus.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.hipparchus.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.hipparchus.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.hipparchus.stat.descriptive

Methods in org.hipparchus.stat.descriptive that return RealMatrix
Modifier and Type	Method	Description
`RealMatrix`	MultivariateSummaryStatistics.`getCovariance()`	Returns the covariance of the available values.
`RealMatrix`	StatisticalMultivariateSummary.`getCovariance()`	Returns the covariance of the available values.

Uses of RealMatrix in org.hipparchus.stat.descriptive.vector

Methods in org.hipparchus.stat.descriptive.vector that return RealMatrix
Modifier and Type	Method	Description
`RealMatrix`	VectorialCovariance.`getResult()`	Get the covariance matrix.

Uses of RealMatrix in org.hipparchus.stat.regression

Methods in org.hipparchus.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()`

Uses of Interfaceorg.hipparchus.linear.RealMatrix

Uses of RealMatrix in org.hipparchus.clustering

Uses of RealMatrix in org.hipparchus.distribution.multivariate

Uses of RealMatrix in org.hipparchus.filtering.kalman

Uses of RealMatrix in org.hipparchus.filtering.kalman.extended

Uses of RealMatrix in org.hipparchus.filtering.kalman.linear

Uses of RealMatrix in org.hipparchus.linear

Uses of RealMatrix in org.hipparchus.optim.nonlinear.scalar

Uses of RealMatrix in org.hipparchus.optim.nonlinear.scalar.noderiv

Uses of RealMatrix in org.hipparchus.optim.nonlinear.vector.leastsquares

Uses of RealMatrix in org.hipparchus.random

Uses of RealMatrix in org.hipparchus.stat.correlation

Uses of RealMatrix in org.hipparchus.stat.descriptive

Uses of RealMatrix in org.hipparchus.stat.descriptive.vector

Uses of RealMatrix in org.hipparchus.stat.regression

Uses of Interface
org.hipparchus.linear.RealMatrix