Uses of Interface
org.hipparchus.linear.RealMatrix

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.filtering.kalman.unscented	Unscented Kalman filter implementation.
org.hipparchus.linear	Linear algebra support.
org.hipparchus.ode.nonstiff	This package provides classes to solve non-stiff Ordinary Differential Equations problems.
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.
org.hipparchus.util	Convenience routines and common data structures used throughout the Hipparchus library.

Uses of RealMatrix in org.hipparchus.clustering

Methods in org.hipparchus.clustering that return RealMatrix

Modifier and Type	Method and 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 and 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 and 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 and 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 and 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 and 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 and 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 and 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 and Description
RealMatrix	LinearEvolution.getControlMatrix() Get the control matrix Bk-1.
RealMatrix	LinearEvolution.getMeasurementJacobian() Get measurement Jacobian.
RealMatrix	LinearEvolution.getProcessNoiseMatrix() Get the process noise matrix Qk-1.
RealMatrix	LinearEvolution.getStateTransitionMatrix() Get the state transition matrix Ak-1.

Constructors in org.hipparchus.filtering.kalman.linear with parameters of type RealMatrix

Constructor and Description
LinearEvolution(RealMatrix stateTransitionMatrix, RealMatrix controlMatrix, RealVector command, RealMatrix processNoiseMatrix, RealMatrix measurementJacobian) Simple constructor.

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

Methods in org.hipparchus.filtering.kalman.unscented that return RealMatrix

Modifier and Type	Method and Description
RealMatrix	UnscentedEvolution.getProcessNoiseMatrix() Get process noise.

Methods in org.hipparchus.filtering.kalman.unscented with parameters of type RealMatrix

Modifier and Type	Method and Description
RealVector	UnscentedProcess.getInnovation(T measurement, RealVector predictedMeasurement, RealVector predictedState, RealMatrix innovationCovarianceMatrix) Get the innovation brought by a measurement.

Constructors in org.hipparchus.filtering.kalman.unscented with parameters of type RealMatrix

Constructor and Description
UnscentedEvolution(double currentTime, RealVector[] currentStates, RealVector[] currentMeasurements, RealMatrix processNoiseMatrix) Constructor.

Uses of RealMatrix in org.hipparchus.linear

Subinterfaces of RealMatrix in org.hipparchus.linear

Modifier and Type	Interface and 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 and 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 and Description
RealMatrix	RealMatrix.add(RealMatrix m) Returns the sum of this and m.
RealMatrix	AbstractRealMatrix.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.
RealMatrix	RealMatrix.copy() Returns a (deep) copy of this.
RealMatrix	Array2DRowRealMatrix.copy() Returns a (deep) copy of this.
abstract RealMatrix	AbstractRealMatrix.copy() Returns a (deep) copy of this.
RealMatrix	DiagonalMatrix.copy() Returns a (deep) copy of this.
static RealMatrix	MatrixUtils.createColumnRealMatrix(double[] columnData) Creates a column RealMatrix using the data from the input array.
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.
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.
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	DiagonalMatrix.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	RealMatrix.getColumnMatrix(int column) Get the entries at the given column index as a column matrix.
RealMatrix	AbstractRealMatrix.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	RiccatiEquationSolverImpl.getK() {inheritDoc}
RealMatrix	RiccatiEquationSolver.getK() Get the linear controller k.
RealMatrix	SemiDefinitePositiveCholeskyDecomposition.getL() Returns the matrix L of the decomposition.
RealMatrix	CholeskyDecomposition.getL() Returns the matrix L of the decomposition.
RealMatrix	LUDecomposition.getL() Returns the matrix L of the decomposition.
RealMatrix	SemiDefinitePositiveCholeskyDecomposition.getLT() Returns the transpose of the matrix L of the decomposition.
RealMatrix	CholeskyDecomposition.getLT() Returns the transpose of the matrix L of the decomposition.
RealMatrix	RiccatiEquationSolverImpl.getP() {inheritDoc}
RealMatrix	RiccatiEquationSolver.getP() Get the solution.
RealMatrix	RRQRDecomposition.getP() Returns the pivot matrix, P, used in the QR Decomposition of matrix A such that AP = QR.
RealMatrix	LUDecomposition.getP() Returns the P rows permutation matrix.
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	RealMatrix.getRowMatrix(int row) Get the entries at the given row index as a row matrix.
RealMatrix	AbstractRealMatrix.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	RealMatrix.getSubMatrix(int[] selectedRows, int[] selectedColumns) Gets a submatrix.
RealMatrix	AbstractRealMatrix.getSubMatrix(int[] selectedRows, int[] selectedColumns) Gets a submatrix.
RealMatrix	RealMatrix.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	AbstractRealMatrix.getSubMatrix(int startRow, int endRow, int startColumn, int endColumn) Gets a submatrix.
RealMatrix	SingularValueDecomposition.getU() Returns the matrix U of the decomposition.
RealMatrix	LUDecomposition.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.
RealMatrix	OrderedEigenDecomposition.getVT() Gets 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.
default RealMatrix	RealMatrix.map(UnivariateFunction function) Acts as if implemented as:
default RealMatrix	RealMatrix.mapToSelf(UnivariateFunction function) Replace each entry by the result of applying the function to it.
static RealMatrix	MatrixUtils.matrixExponential(RealMatrix rm) Computes the matrix exponential of the given matrix.
RealMatrix	RealMatrix.multiply(RealMatrix m) Returns the result of postmultiplying this by m.
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	Array2DRowRealMatrix.multiplyTransposed(Array2DRowRealMatrix 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	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.
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	RealMatrix.power(int p) Returns the result of multiplying this with itself p times.
RealMatrix	AbstractRealMatrix.power(int p) Returns the result of multiplying this with itself p times.
RealMatrix	RealMatrix.preMultiply(RealMatrix m) Returns the result of premultiplying this by m.
RealMatrix	AbstractRealMatrix.preMultiply(RealMatrix m) Returns the result of premultiplying this by m.
RealMatrix	RealMatrix.scalarAdd(double d) Returns the result of adding d to each entry of this.
RealMatrix	AbstractRealMatrix.scalarAdd(double d) Returns the result of adding d to each entry of this.
RealMatrix	RealMatrix.scalarMultiply(double d) Returns the result of multiplying each entry of this by d.
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	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	RealMatrix.subtract(RealMatrix m) Returns this minus m.
RealMatrix	AbstractRealMatrix.subtract(RealMatrix m) Returns this minus m.
RealMatrix	RealMatrix.transpose() Returns the transpose of this matrix.
RealMatrix	AbstractRealMatrix.transpose() Returns the transpose of this matrix.
RealMatrix	Array2DRowRealMatrix.transposeMultiply(Array2DRowRealMatrix 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.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.
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 and Description
RealMatrix	RealMatrix.add(RealMatrix m) Returns the sum of this and m.
RealMatrix	AbstractRealMatrix.add(RealMatrix m) Returns the sum of this and m.
BlockRealMatrix	BlockRealMatrix.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	MatrixDecomposer.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.
DecompositionSolver	QRDecomposer.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.
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.
static RealMatrix	MatrixUtils.matrixExponential(RealMatrix rm) Computes the matrix exponential of the given matrix.
RealMatrix	RealMatrix.multiply(RealMatrix m) Returns the result of postmultiplying this by m.
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.
BlockRealMatrix	BlockRealMatrix.multiply(RealMatrix m) Returns the result of postmultiplying this by m.
RealMatrix	OpenMapRealMatrix.multiply(RealMatrix m) Returns the result of postmultiplying this by m.
default RealMatrix	RealMatrix.multiplyTransposed(RealMatrix 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.
BlockRealMatrix	BlockRealMatrix.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.
RealMatrix	RealMatrix.preMultiply(RealMatrix m) Returns the result of premultiplying this by m.
RealMatrix	AbstractRealMatrix.preMultiply(RealMatrix m) Returns the result of premultiplying this by m.
static void	MatrixUtils.serializeRealMatrix(RealMatrix matrix, ObjectOutputStream oos) Serialize a RealMatrix.
void	RealMatrix.setColumnMatrix(int column, RealMatrix matrix) Sets the specified column of this matrix to the entries of the specified column matrix.
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.setRowMatrix(int row, RealMatrix matrix) Sets the specified row of this matrix to the entries of the specified row 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.
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	RealMatrix.subtract(RealMatrix m) Returns this minus m.
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.
default RealMatrix	RealMatrix.transposeMultiply(RealMatrix 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.
BlockRealMatrix	BlockRealMatrix.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.

Constructors in org.hipparchus.linear with parameters of type RealMatrix

Constructor and 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.
ComplexEigenDecomposition(RealMatrix matrix, double eigenVectorsEquality, double epsilon, double epsilonAVVDCheck) Constructor for decomposition.
EigenDecomposition(RealMatrix matrix) Calculates the eigen decomposition of the given real matrix.
EigenDecomposition(RealMatrix matrix, double epsilon) 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.
OrderedComplexEigenDecomposition(RealMatrix matrix, double eigenVectorsEquality, double epsilon, double epsilonAVVDCheck) Constructor for 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.
SemiDefinitePositiveCholeskyDecomposition(RealMatrix matrix) Calculates the Cholesky decomposition of the given matrix.
SemiDefinitePositiveCholeskyDecomposition(RealMatrix matrix, double positivityThreshold) Calculates the Cholesky decomposition of the given matrix.
SingularValueDecomposition(RealMatrix matrix) Calculates the compact Singular Value Decomposition of the given matrix.

Uses of RealMatrix in org.hipparchus.ode.nonstiff

Methods in org.hipparchus.ode.nonstiff with parameters of type RealMatrix

Modifier and Type	Method and Description
protected double	AdamsMoultonIntegrator.errorEstimation(double[] previousState, double predictedTime, double[] predictedState, double[] predictedScaled, RealMatrix predictedNordsieck) Estimate error.
protected abstract double	AdamsIntegrator.errorEstimation(double[] previousState, double predictedTime, double[] predictedState, double[] predictedScaled, RealMatrix predictedNordsieck) Estimate error.
protected double	AdamsBashforthIntegrator.errorEstimation(double[] previousState, double predictedTime, double[] predictedState, double[] predictedScaled, RealMatrix predictedNordsieck) Estimate error.

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

Constructors in org.hipparchus.optim.nonlinear.scalar with parameters of type RealMatrix

Constructor and 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 and 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 and Description
RealMatrix	ValueAndJacobianFunction.computeJacobian(double[] params) Compute the Jacobian.
RealMatrix	LeastSquaresProblem.Evaluation.getCovariances(double threshold) Get the covariance matrix of the optimized parameters.
RealMatrix	AbstractEvaluation.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 and 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 and Description
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.
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.
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.
SequentialGaussNewtonOptimizer	SequentialGaussNewtonOptimizer.withAPrioriData(RealVector aPrioriState, RealMatrix aPrioriCovariance) Configure from a priori state and covariance.

Uses of RealMatrix in org.hipparchus.random

Methods in org.hipparchus.random that return RealMatrix

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

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

Constructor and 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 and Description
RealMatrix	SpearmansCorrelation.computeCorrelationMatrix(double[][] matrix) Computes the Spearman's rank correlation matrix for the columns of the input rectangular array.
RealMatrix	KendallsCorrelation.computeCorrelationMatrix(double[][] matrix) Computes the Kendall's Tau rank correlation matrix for the columns of the input rectangular array.
RealMatrix	PearsonsCorrelation.computeCorrelationMatrix(double[][] data) Computes the 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.
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[]).
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	SpearmansCorrelation.getCorrelationMatrix() Calculate the Spearman Rank Correlation Matrix.
RealMatrix	KendallsCorrelation.getCorrelationMatrix() Returns the correlation matrix.
RealMatrix	PearsonsCorrelation.getCorrelationMatrix() Returns the 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	StorelessCovariance.getCovarianceMatrix() Returns the covariance matrix
RealMatrix	Covariance.getCovarianceMatrix() Returns the covariance matrix

Methods in org.hipparchus.stat.correlation with parameters of type RealMatrix

Modifier and Type	Method and Description
RealMatrix	SpearmansCorrelation.computeCorrelationMatrix(RealMatrix matrix) Computes the Spearman's rank correlation matrix for the columns of the input matrix.
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[]).
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 and 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 and Description
RealMatrix	StatisticalMultivariateSummary.getCovariance() Returns the covariance of the available values.
RealMatrix	MultivariateSummaryStatistics.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 and 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 and Description
protected RealMatrix	GLSMultipleLinearRegression.calculateBetaVariance() Calculates the variance on the beta.
protected RealMatrix	OLSMultipleLinearRegression.calculateBetaVariance() Calculates the variance-covariance matrix of the regression parameters.
protected abstract RealMatrix	AbstractMultipleLinearRegression.calculateBetaVariance() Calculates the beta variance of multiple linear regression in matrix notation.
RealMatrix	OLSMultipleLinearRegression.calculateHat() Compute the "hat" matrix.
protected RealMatrix	GLSMultipleLinearRegression.getOmegaInverse() Get the inverse of the covariance.
protected RealMatrix	AbstractMultipleLinearRegression.getX()

Uses of RealMatrix in org.hipparchus.util

Methods in org.hipparchus.util with parameters of type RealMatrix

Modifier and Type	Method and Description
RealVector[]	UnscentedTransformProvider.unscentedTransform(RealVector state, RealMatrix covariance) Perform the unscented transform from a state and its covariance.
RealVector[]	AbstractUnscentedTransform.unscentedTransform(RealVector state, RealMatrix covariance) Perform the unscented transform from a state and its covariance.