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

Packages that use RealMatrix
org.apache.commons.math3.distribution | Implementations of common discrete and continuous distributions.
org.apache.commons.math3.filter | Implementations of common discrete-time linear filters.
org.apache.commons.math3.linear | Linear algebra support.
org.apache.commons.math3.optim.nonlinear.scalar | Algorithms for optimizing a scalar function.
org.apache.commons.math3.optim.nonlinear.scalar.noderiv | This package provides optimization algorithms that do not require derivatives.
org.apache.commons.math3.optim.nonlinear.vector | Algorithms for optimizing a vector function.
org.apache.commons.math3.optim.nonlinear.vector.jacobian | This package provides optimization algorithms that require derivatives.
org.apache.commons.math3.optimization | All classes and sub-packages of this package are deprecated.
org.apache.commons.math3.optimization.direct | This package provides optimization algorithms that don't require derivatives.
org.apache.commons.math3.optimization.general | This package provides optimization algorithms that require derivatives.
org.apache.commons.math3.random | Random number and random data generators.
org.apache.commons.math3.stat.correlation | Correlations/Covariance computations.
org.apache.commons.math3.stat.descriptive | Generic univariate summary statistic objects.
org.apache.commons.math3.stat.descriptive.moment | Summary statistics based on moments.
org.apache.commons.math3.stat.regression | Statistical routines involving multivariate data.

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

Methods in org.apache.commons.math3.distribution that return RealMatrix
`RealMatrix` | `MultivariateNormalDistribution.getCovariances()` Gets the covariance matrix.

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

Methods in org.apache.commons.math3.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` | `DefaultMeasurementModel.getMeasurementMatrix()` Returns the measurement matrix.
`RealMatrix` | `MeasurementModel.getMeasurementMatrix()` Returns the measurement matrix.
`RealMatrix` | `DefaultMeasurementModel.getMeasurementNoise()` Returns the measurement noise matrix.
`RealMatrix` | `MeasurementModel.getMeasurementNoise()` Returns the measurement noise matrix.
`RealMatrix` | `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.math3.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.math3.linear

Subinterfaces of RealMatrix in org.apache.commons.math3.linear
`interface` | `SparseRealMatrix` Deprecated. As of version 3.1, this class is deprecated, for reasons exposed in this JIRA ticket. This class will be removed in version 4.0.

Classes in org.apache.commons.math3.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` | `DiagonalMatrix` Implementation of a diagonal matrix.
`class` | `OpenMapRealMatrix` Deprecated. As of version 3.1, this class is deprecated, for reasons exposed in this JIRA ticket. This class will be removed in version 4.0.

Methods in org.apache.commons.math3.linear that return RealMatrix
`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.
`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.
`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.
`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.
`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 inverse (or pseudo-inverse) of the decomposed matrix.
`RealMatrix` | `CholeskyDecomposition.getL()` Returns the matrix L of the decomposition.
`RealMatrix` | `LUDecomposition.getL()` Returns the matrix L of the decomposition.
`RealMatrix` | `CholeskyDecomposition.getLT()` Returns the transpose of the matrix L of the decomposition.
`RealMatrix` | `LUDecomposition.getP()` Returns the P rows permutation matrix.
`RealMatrix` | `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` | `RealMatrix.getSubMatrix(int[] selectedRows, int[] selectedColumns)` Gets a submatrix.
`RealMatrix` | `AbstractRealMatrix.getSubMatrix(int startRow, int endRow, int startColumn, int endColumn)` Gets a submatrix.
`RealMatrix` | `RealMatrix.getSubMatrix(int 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` | `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` | `RealMatrix.multiply(RealMatrix m)` Returns the result of postmultiplying `this` by `m`.
`RealMatrix` | `OpenMapRealMatrix.multiply(RealMatrix m)` Deprecated. Returns the result of postmultiplying `this` by `m`.
`RealMatrix` | `ArrayRealVector.outerProduct(RealVector v)` Compute the outer product.
`RealMatrix` | `RealVector.outerProduct(RealVector v)` Compute the outer product.
`RealMatrix` | `RealMatrixFormat.parse(String source)` Parse a string to produce a `RealMatrix` object.
`RealMatrix` | `RealMatrixFormat.parse(String source, ParsePosition pos)` Parse a string to produce a `RealMatrix` object.
`RealMatrix` | `AbstractRealMatrix.power(int p)` Returns the result of multiplying `this` with itself `p` times.
`RealMatrix` | `RealMatrix.power(int p)` Returns the result of multiplying `this` with itself `p` times.
`RealMatrix` | `AbstractRealMatrix.preMultiply(RealMatrix m)` Returns the result of premultiplying `this` by `m`.
`RealMatrix` | `RealMatrix.preMultiply(RealMatrix m)` Returns the result of premultiplying `this` by `m`.
`RealMatrix` | `AbstractRealMatrix.scalarAdd(double d)` Returns the result of adding `d` to each entry of `this`.
`RealMatrix` | `RealMatrix.scalarAdd(double d)` Returns the result of adding `d` to each entry of `this`.
`RealMatrix` | `AbstractRealMatrix.scalarMultiply(double d)` Returns the result of multiplying each entry of `this` by `d`.
`RealMatrix` | `RealMatrix.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` | `AbstractRealMatrix.subtract(RealMatrix m)` Returns `this` minus `m`.
`RealMatrix` | `RealMatrix.subtract(RealMatrix m)` Returns `this` minus `m`.
`RealMatrix` | `AbstractRealMatrix.transpose()` Returns the transpose of this matrix.
`RealMatrix` | `RealMatrix.transpose()` Returns the transpose of this matrix.

Methods in org.apache.commons.math3.linear with parameters of type RealMatrix
`RealMatrix` | `AbstractRealMatrix.add(RealMatrix m)` Returns the sum of `this` and `m`.
`RealMatrix` | `RealMatrix.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.
`static void` | `MatrixUtils.checkSymmetric(RealMatrix matrix, double eps)` Checks whether a matrix is symmetric.
`String` | `RealMatrixFormat.format(RealMatrix m)` This method calls `RealMatrixFormat.format(RealMatrix,StringBuffer,FieldPosition)`.
`StringBuffer` | `RealMatrixFormat.format(RealMatrix matrix, StringBuffer toAppendTo, FieldPosition pos)` Formats a `RealMatrix` object to produce a string.
`static boolean` | `MatrixUtils.isSymmetric(RealMatrix matrix, double eps)` Checks whether a matrix is symmetric.
`RealMatrix` | `AbstractRealMatrix.multiply(RealMatrix m)` Returns the result of postmultiplying `this` by `m`.
`RealMatrix` | `DiagonalMatrix.multiply(RealMatrix m)` Returns the result of postmultiplying `this` by `m`.
`RealMatrix` | `RealMatrix.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)` Deprecated. Returns the result of postmultiplying `this` by `m`.
`RealMatrix` | `AbstractRealMatrix.preMultiply(RealMatrix m)` Returns the result of premultiplying `this` by `m`.
`RealMatrix` | `RealMatrix.preMultiply(RealMatrix m)` Returns the result of premultiplying `this` by `m`.
`static void` | `MatrixUtils.serializeRealMatrix(RealMatrix matrix, ObjectOutputStream oos)` Serialize a `RealMatrix`.
`void` | `AbstractRealMatrix.setColumnMatrix(int column, RealMatrix matrix)` Sets the specified `column` of `this` matrix to the entries of the specified column `matrix`.
`void` | `RealMatrix.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` | `AbstractRealMatrix.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`.
`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` | `AbstractRealMatrix.subtract(RealMatrix m)` Returns `this` minus `m`.
`RealMatrix` | `RealMatrix.subtract(RealMatrix m)` Returns `this` minus `m`.
`BlockRealMatrix` | `BlockRealMatrix.subtract(RealMatrix m)` Returns `this` minus `m`.
`OpenMapRealMatrix` | `OpenMapRealMatrix.subtract(RealMatrix m)` Deprecated. Returns `this` minus `m`.

Constructors in org.apache.commons.math3.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)` Calculates the eigen decomposition of the given real matrix.
`EigenDecomposition(RealMatrix matrix, double splitTolerance)` Deprecated. in 3.1 (to be removed in 4.0) due to unused parameter
`LUDecomposition(RealMatrix matrix)` Calculates the LU-decomposition of the given matrix.
`LUDecomposition(RealMatrix matrix, double singularityThreshold)` Calculates the LU-decomposition of the given matrix.
`QRDecomposition(RealMatrix matrix)` Calculates the QR-decomposition of the given matrix.
`QRDecomposition(RealMatrix matrix, double threshold)` Calculates the QR-decomposition of the given matrix.
`RectangularCholeskyDecomposition(RealMatrix matrix)` Decompose a symmetric positive semidefinite matrix.
`RectangularCholeskyDecomposition(RealMatrix matrix, double small)` Decompose a symmetric positive semidefinite matrix.
`SingularValueDecomposition(RealMatrix matrix)` Calculates the compact Singular Value Decomposition of the given matrix.

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

Constructors in org.apache.commons.math3.optim.nonlinear.scalar with parameters of type RealMatrix
`LeastSquaresConverter(MultivariateVectorFunction function, double[] observations, RealMatrix scale)` Builds a simple converter for correlated residuals with the specified weights.

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

Methods in org.apache.commons.math3.optim.nonlinear.scalar.noderiv that return types with arguments of type RealMatrix
`List<RealMatrix>` | `CMAESOptimizer.getStatisticsDHistory()`
`List<RealMatrix>` | `CMAESOptimizer.getStatisticsMeanHistory()`

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

Methods in org.apache.commons.math3.optim.nonlinear.vector that return RealMatrix
`RealMatrix` | `MultivariateVectorOptimizer.getWeight()` Gets the weight matrix of the observations.
`RealMatrix` | `Weight.getWeight()` Gets the initial guess.

Constructors in org.apache.commons.math3.optim.nonlinear.vector with parameters of type RealMatrix
`Weight(RealMatrix weight)`

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

Methods in org.apache.commons.math3.optim.nonlinear.vector.jacobian that return RealMatrix
`protected RealMatrix` | `AbstractLeastSquaresOptimizer.computeWeightedJacobian(double[] params)` Computes the weighted Jacobian matrix.
`RealMatrix` | `AbstractLeastSquaresOptimizer.getWeightSquareRoot()` Gets the square-root of the weight matrix.

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

Methods in org.apache.commons.math3.optimization that return RealMatrix
`RealMatrix` | `Weight.getWeight()` Deprecated. Gets the initial guess.

Constructors in org.apache.commons.math3.optimization with parameters of type RealMatrix
`LeastSquaresConverter(MultivariateVectorFunction function, double[] observations, RealMatrix scale)` Deprecated. Build a simple converter for correlated residuals with the specific weights.
`Weight(RealMatrix weight)` Deprecated.

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

Methods in org.apache.commons.math3.optimization.direct that return RealMatrix
`RealMatrix` | `BaseAbstractMultivariateVectorOptimizer.getWeight()` Deprecated. Gets the weight matrix of the observations.

Methods in org.apache.commons.math3.optimization.direct that return types with arguments of type RealMatrix
`List<RealMatrix>` | `CMAESOptimizer.getStatisticsDHistory()` Deprecated.
`List<RealMatrix>` | `CMAESOptimizer.getStatisticsMeanHistory()` Deprecated.

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

Methods in org.apache.commons.math3.optimization.general that return RealMatrix
`protected RealMatrix` | `AbstractLeastSquaresOptimizer.computeWeightedJacobian(double[] params)` Deprecated. Computes the Jacobian matrix.
`RealMatrix` | `AbstractLeastSquaresOptimizer.getWeightSquareRoot()` Deprecated. Gets the square-root of the weight matrix.

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

Methods in org.apache.commons.math3.random that return RealMatrix
`RealMatrix` | `CorrelatedRandomVectorGenerator.getRootMatrix()` Get the root of the covariance matrix.

Constructors in org.apache.commons.math3.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.math3.stat.correlation

Methods in org.apache.commons.math3.stat.correlation that return RealMatrix
`RealMatrix` | `PearsonsCorrelation.computeCorrelationMatrix(double[][] data)` Computes the correlation matrix for the columns of the input rectangular array.
`RealMatrix` | `SpearmansCorrelation.computeCorrelationMatrix(double[][] matrix)` Computes the Spearman's rank 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.
`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` | `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` | `StorelessCovariance.getCovarianceMatrix()` Returns the covariance matrix
`RealMatrix` | `Covariance.getCovarianceMatrix()` Returns the covariance matrix

Methods in org.apache.commons.math3.stat.correlation with parameters of type RealMatrix
`RealMatrix` | `PearsonsCorrelation.computeCorrelationMatrix(RealMatrix matrix)` Computes the correlation matrix for the columns of the input matrix.
`RealMatrix` | `SpearmansCorrelation.computeCorrelationMatrix(RealMatrix matrix)` Computes the Spearman's rank correlation matrix for the columns of the input matrix.
`protected RealMatrix` | `Covariance.computeCovarianceMatrix(RealMatrix matrix)` Create a covariance matrix from a matrix whose columns represent covariates.
`protected RealMatrix` | `Covariance.computeCovarianceMatrix(RealMatrix matrix, boolean biasCorrected)` Compute a covariance matrix from a matrix whose columns represent covariates.
`RealMatrix` | `PearsonsCorrelation.covarianceToCorrelation(RealMatrix covarianceMatrix)` Derives a correlation matrix from a covariance matrix.

Constructors in org.apache.commons.math3.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.math3.stat.descriptive

Methods in org.apache.commons.math3.stat.descriptive that return RealMatrix
`RealMatrix` | `StatisticalMultivariateSummary.getCovariance()` Returns the covariance of the available values.
`RealMatrix` | `SynchronizedMultivariateSummaryStatistics.getCovariance()` Returns the covariance matrix of the values that have been added.
`RealMatrix` | `MultivariateSummaryStatistics.getCovariance()` Returns the covariance matrix of the values that have been added.

Uses of RealMatrix in org.apache.commons.math3.stat.descriptive.moment

Methods in org.apache.commons.math3.stat.descriptive.moment that return RealMatrix
`RealMatrix` | `VectorialCovariance.getResult()` Get the covariance matrix.

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

Methods in org.apache.commons.math3.stat.regression that return RealMatrix
`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()`

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