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

Packages that use RealMatrix

org.apache.commons.math.filter	Implementations of common discrete-time linear filters.
org.apache.commons.math.linear	Linear algebra support.
org.apache.commons.math.optimization	This package provides common interfaces for the optimization algorithms provided in sub-packages.
org.apache.commons.math.optimization.direct	This package provides optimization algorithms that don't require derivatives.
org.apache.commons.math.random	Random number and random data generators.
org.apache.commons.math.stat.correlation	Correlations/Covariance computations.
org.apache.commons.math.stat.descriptive	Generic univariate summary statistic objects.
org.apache.commons.math.stat.descriptive.moment	Summary statistics based on moments.
org.apache.commons.math.stat.regression	Statistical routines involving multivariate data.

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

Methods in org.apache.commons.math.filter that return RealMatrix

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

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

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.math.linear

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

interface

SparseRealMatrix Marker interface for RealMatrix implementations that require sparse backing storage

Classes in org.apache.commons.math.linear that implement RealMatrix

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	OpenMapRealMatrix Sparse matrix implementation based on an open addressed map.

Methods in org.apache.commons.math.linear that return RealMatrix

RealMatrix	RealMatrix.add(RealMatrix m) Compute the sum of this and m.
RealMatrix	AbstractRealMatrix.add(RealMatrix m) Compute the sum of this and m.
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.
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.
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() Returns the block diagonal matrix D of the decomposition.
RealMatrix	QRDecomposition.getH() Returns the Householder reflector vectors.
RealMatrix	PivotingQRDecomposition.getH()
RealMatrix	DecompositionSolver.getInverse() Get the inverse (or pseudo-inverse) of the decomposed matrix.
RealMatrix	LUDecomposition.getL() Returns the matrix L of the decomposition.
RealMatrix	CholeskyDecomposition.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	PivotingQRDecomposition.getPermutationMatrix()
RealMatrix	QRDecomposition.getQ() Returns the matrix Q of the decomposition.
RealMatrix	PivotingQRDecomposition.getQ() Returns the matrix Q of the decomposition.
RealMatrix	QRDecomposition.getQT() Returns the transpose of the matrix Q of the decomposition.
RealMatrix	PivotingQRDecomposition.getQT() Returns the transpose of the matrix Q of the decomposition.
RealMatrix	QRDecomposition.getR() Returns the matrix R of the decomposition.
RealMatrix	PivotingQRDecomposition.getR() Returns the matrix R of the decomposition.
RealMatrix	RectangularCholeskyDecomposition.getRootMatrix() Get the root of the covariance matrix.
RealMatrix	RealMatrix.getRowMatrix(int row) Geet the entries at the given row index as a row matrix.
RealMatrix	AbstractRealMatrix.getRowMatrix(int row) Geet the entries at the given row index as a row matrix.
RealMatrix	SingularValueDecomposition.getS() Returns the diagonal matrix Σ of the decomposition.
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	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	SingularValueDecomposition.getV() Returns the matrix V of the decomposition.
RealMatrix	EigenDecomposition.getV() Returns the matrix V of the decomposition.
RealMatrix	SingularValueDecomposition.getVT() Returns the transpose of the matrix V of the decomposition.
RealMatrix	EigenDecomposition.getVT() Returns the transpose of the matrix V of the decomposition.
RealMatrix	RealMatrix.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	AbstractRealMatrix.multiply(RealMatrix m) Returns the result of postmultiplying this by m.
RealMatrix	RealVector.outerProduct(RealVector v) Compute the outer product.
RealMatrix	ArrayRealVector.outerProduct(RealVector v) Compute the outer product.
RealMatrix	RealMatrix.power(int p) Returns the result multiplying this with itself p times.
RealMatrix	AbstractRealMatrix.power(int p) Returns the result multiplying this with itself p times.
RealMatrix	RealMatrix.preMultiply(RealMatrix m) Returns the result premultiplying this by m.
RealMatrix	AbstractRealMatrix.preMultiply(RealMatrix m) Returns the result 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 multiplying each entry of this by d.
RealMatrix	BlockRealMatrix.scalarMultiply(double d) Returns the result multiplying each entry of this by d.
RealMatrix	AbstractRealMatrix.scalarMultiply(double d) Returns the result multiplying each entry of this by d.
RealMatrix	DecompositionSolver.solve(RealMatrix b) Solve the linear equation A × X = B for matrices A.
RealMatrix	RealMatrix.subtract(RealMatrix m) Compute this minus m.
RealMatrix	AbstractRealMatrix.subtract(RealMatrix m) Compute this minus m.
RealMatrix	RealMatrix.transpose() Returns the transpose of this matrix.
RealMatrix	AbstractRealMatrix.transpose() Returns the transpose of this matrix.

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

RealMatrix	RealMatrix.add(RealMatrix m) Compute the sum of this and m.
BlockRealMatrix	BlockRealMatrix.add(RealMatrix m) Compute the sum of this and m.
RealMatrix	AbstractRealMatrix.add(RealMatrix m) Compute the sum of this and m.
RealMatrix	RealMatrix.multiply(RealMatrix m) Returns the result of postmultiplying this by m.
RealMatrix	OpenMapRealMatrix.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	AbstractRealMatrix.multiply(RealMatrix m) Returns the result of postmultiplying this by m.
RealMatrix	RealMatrix.preMultiply(RealMatrix m) Returns the result premultiplying this by m.
RealMatrix	AbstractRealMatrix.preMultiply(RealMatrix m) Returns the result premultiplying this by m.
static void	MatrixUtils.serializeRealMatrix(RealMatrix matrix, java.io.ObjectOutputStream oos) Serialize a RealMatrix.
void	RealMatrix.setColumnMatrix(int column, RealMatrix matrix) Set the entries at the given column index as a column matrix.
void	BlockRealMatrix.setColumnMatrix(int column, RealMatrix matrix) Set the entries at the given column index as a column matrix.
void	AbstractRealMatrix.setColumnMatrix(int column, RealMatrix matrix) Set the entries at the given column index as a column matrix.
void	RealMatrix.setRowMatrix(int row, RealMatrix matrix) Set the entries at the given row index as a row matrix.
void	BlockRealMatrix.setRowMatrix(int row, RealMatrix matrix) Set the entries at the given row index as a row matrix.
void	AbstractRealMatrix.setRowMatrix(int row, RealMatrix matrix) Set the entries at the given row index as a 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) Compute this minus m.
OpenMapRealMatrix	OpenMapRealMatrix.subtract(RealMatrix m) Compute this minus m.
BlockRealMatrix	BlockRealMatrix.subtract(RealMatrix m) Compute this minus m.
RealMatrix	AbstractRealMatrix.subtract(RealMatrix m) Compute this minus m.

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

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, double splitTolerance)
Calculates the eigen decomposition of the given symmetric 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.

PivotingQRDecomposition(RealMatrix matrix)

PivotingQRDecomposition(RealMatrix matrix, boolean allowPivot)

PivotingQRDecomposition(RealMatrix matrix, double qrRankingThreshold, boolean allowPivot)

QRDecomposition(RealMatrix matrix)
Calculates the QR-decomposition of the given matrix.

RectangularCholeskyDecomposition(RealMatrix matrix, double small)
Decompose a symmetric positive semidefinite matrix.

SingularValueDecomposition(RealMatrix matrix)
Calculates the compact Singular Value Decomposition of the given matrix.

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

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

LeastSquaresConverter(MultivariateVectorialFunction function, double[] observations, RealMatrix scale)
Build a simple converter for correlated residuals with the specific weights.

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

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

java.util.List<RealMatrix>	CMAESOptimizer.getStatisticsDHistory()
java.util.List<RealMatrix>	CMAESOptimizer.getStatisticsMeanHistory()

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

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

RealMatrix

CorrelatedRandomVectorGenerator.getRootMatrix() Get the root of the covariance matrix.

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

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.math.stat.correlation

Methods in org.apache.commons.math.stat.correlation that return RealMatrix

RealMatrix	SpearmansCorrelation.computeCorrelationMatrix(double[][] matrix) Computes the Spearman's 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	PearsonsCorrelation.computeCorrelationMatrix(RealMatrix matrix) Computes the 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	SpearmansCorrelation.getCorrelationMatrix() Calculate the Spearman Rank 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.
RealMatrix	StorelessCovariance.getCovarianceMatrix()
RealMatrix	Covariance.getCovarianceMatrix() Returns the covariance matrix

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

RealMatrix	SpearmansCorrelation.computeCorrelationMatrix(RealMatrix matrix) Computes the Spearman's 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.
protected RealMatrix	Covariance.computeCovarianceMatrix(RealMatrix matrix) Create a covariance matrix from a matrix whose columns represent covariates.
protected RealMatrix	Covariance.computeCovarianceMatrix(RealMatrix matrix, boolean biasCorrected) Compute a covariance matrix from a matrix whose columns represent covariates.
RealMatrix	PearsonsCorrelation.covarianceToCorrelation(RealMatrix covarianceMatrix) Derives a correlation matrix from a covariance matrix.

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

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.

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.math.stat.descriptive

Methods in org.apache.commons.math.stat.descriptive that return RealMatrix

RealMatrix	SynchronizedMultivariateSummaryStatistics.getCovariance() Returns the covariance matrix of the values that have been added.
RealMatrix	StatisticalMultivariateSummary.getCovariance() Returns the covariance of the available values.
RealMatrix	MultivariateSummaryStatistics.getCovariance() Returns the covariance matrix of the values that have been added.

Uses of RealMatrix in org.apache.commons.math.stat.descriptive.moment

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

RealMatrix

VectorialCovariance.getResult() Get the covariance matrix.

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

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

protected RealMatrix

AbstractMultipleLinearRegression.X X sample data.

Methods in org.apache.commons.math.stat.regression that return RealMatrix

protected RealMatrix	OLSMultipleLinearRegression.calculateBetaVariance() Calculates the variance-covariance matrix of the regression parameters.
protected RealMatrix	GLSMultipleLinearRegression.calculateBetaVariance() Calculates the variance on the beta.
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.