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

- Packages that use RealMatrix
  Package | Description
  --- | ---
  org.apache.commons.math3.filter | Implementations of common discrete-time linear filters.
  org.apache.commons.math3.linear | Linear algebra support.
  org.apache.commons.math3.optimization | This package provides common interfaces for the optimization algorithms provided in sub-packages.
  org.apache.commons.math3.optimization.direct | This package provides optimization algorithms that don't 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.filter

    Methods in org.apache.commons.math3.filter that return RealMatrix
    Modifier and Type | Method and Description
    --- | ---
    `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
    Constructor and Description
    `DefaultMeasurementModel(RealMatrix measMatrix, RealMatrix measNoise)` Create a new `MeasurementModel`, taking `RealMatrix` objects as input parameters for the respective measurement matrix and noise.
    `DefaultProcessModel(RealMatrix stateTransition, RealMatrix control, RealMatrix processNoise, RealVector initialStateEstimate, RealMatrix initialErrorCovariance)` Create a new `ProcessModel`, taking double arrays as input parameters.

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

    Subinterfaces of RealMatrix in org.apache.commons.math3.linear
    Modifier and Type | Interface and Description
    --- | ---
    `interface` | `SparseRealMatrix` Marker interface for `RealMatrix` implementations that require sparse backing storage

    Classes in org.apache.commons.math3.linear that implement RealMatrix
    Modifier and Type | Class 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` | `OpenMapRealMatrix` Sparse matrix implementation based on an open addressed map.

    Methods in org.apache.commons.math3.linear that return RealMatrix
    Modifier and Type | Method and Description
    --- | ---
    `RealMatrix` | AbstractRealMatrix.`add(RealMatrix m)` Compute the sum of this and m.
    `RealMatrix` | RealMatrix.`add(RealMatrix m)` Compute the sum of this and m.
    `abstract RealMatrix` | AbstractRealMatrix.`copy()` Returns a (deep) copy of this.
    `RealMatrix` | RealMatrix.`copy()` Returns a (deep) copy of this.
    `RealMatrix` | Array2DRowRealMatrix.`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` | 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.
    `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)` Geet the entries at the given row index as a row matrix.
    `RealMatrix` | RealMatrix.`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` | 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` | 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` | SingularValueDecomposition.`getV()` Returns the matrix V of the decomposition.
    `RealMatrix` | EigenDecomposition.`getV()` Gets the matrix V of the decomposition.
    `RealMatrix` | SingularValueDecomposition.`getVT()` Returns the transpose of the matrix V of the decomposition.
    `RealMatrix` | EigenDecomposition.`getVT()` Gets the transpose of the matrix V of the decomposition.
    `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` | RealMatrix.`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` | AbstractRealMatrix.`power(int p)` Returns the result multiplying this with itself `p` times.
    `RealMatrix` | RealMatrix.`power(int p)` Returns the result multiplying this with itself `p` times.
    `RealMatrix` | AbstractRealMatrix.`preMultiply(RealMatrix m)` Returns the result premultiplying this by `m`.
    `RealMatrix` | RealMatrix.`preMultiply(RealMatrix m)` Returns the result 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 multiplying each entry of this by d.
    `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` | DecompositionSolver.`solve(RealMatrix b)` Solve the linear equation A × X = B for matrices A.
    `RealMatrix` | AbstractRealMatrix.`subtract(RealMatrix m)` Compute this minus m.
    `RealMatrix` | RealMatrix.`subtract(RealMatrix m)` Compute this minus m.
    `RealMatrix` | AbstractRealMatrix.`transpose()` Returns the transpose of this matrix.
    `RealMatrix` | RealMatrix.`transpose()` Returns the transpose of this matrix.

    Methods in org.apache.commons.math3.linear with parameters of type RealMatrix
    Modifier and Type | Method and Description
    --- | ---
    `RealMatrix` | AbstractRealMatrix.`add(RealMatrix m)` Compute the sum of this and m.
    `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` | 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` | 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` | AbstractRealMatrix.`preMultiply(RealMatrix m)` Returns the result premultiplying this by `m`.
    `RealMatrix` | RealMatrix.`preMultiply(RealMatrix m)` Returns the result premultiplying this by `m`.
    `static void` | MatrixUtils.`serializeRealMatrix(RealMatrix matrix, ObjectOutputStream oos)` Serialize a `RealMatrix`.
    `void` | AbstractRealMatrix.`setColumnMatrix(int column, RealMatrix matrix)` Set the entries at the given column index as a column matrix.
    `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.`setRowMatrix(int row, RealMatrix matrix)` Set the entries at the given row index as a row 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.
    `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`.
    `OpenMapRealMatrix` | OpenMapRealMatrix.`subtract(RealMatrix m)` Compute this minus m.
    `RealMatrix` | AbstractRealMatrix.`subtract(RealMatrix m)` Compute this minus m.
    `RealMatrix` | RealMatrix.`subtract(RealMatrix m)` Compute this minus m.
    `BlockRealMatrix` | BlockRealMatrix.`subtract(RealMatrix m)` Compute this minus m.

    Constructors in org.apache.commons.math3.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.
    `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.
    `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, 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.optimization

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

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

    Methods in org.apache.commons.math3.optimization.direct 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.apache.commons.math3.random

    Methods in org.apache.commons.math3.random that return RealMatrix
    Modifier and Type | Method and Description
    --- | ---
    `RealMatrix` | CorrelatedRandomVectorGenerator.`getRootMatrix()` Get the root of the covariance matrix.

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

    Methods in org.apache.commons.math3.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` | 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. `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.apache.commons.math3.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` | 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.math3.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.
    `PearsonsCorrelation(RealMatrix matrix)` Create a PearsonsCorrelation from a RealMatrix whose columns represent variables to be correlated.
    `PearsonsCorrelation(RealMatrix covarianceMatrix, int numberOfObservations)` Create a PearsonsCorrelation from a covariance matrix.
    `SpearmansCorrelation(RealMatrix dataMatrix)` Create a SpearmansCorrelation from the given data matrix.
    `SpearmansCorrelation(RealMatrix dataMatrix, RankingAlgorithm rankingAlgorithm)` Create a SpearmansCorrelation with the given input data matrix and ranking algorithm.

  - ### Uses of RealMatrix in org.apache.commons.math3.stat.descriptive

    Methods in org.apache.commons.math3.stat.descriptive that return RealMatrix
    Modifier and Type | Method and Description
    --- | ---
    `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
    Modifier and Type | Method and Description
    --- | ---
    `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
    Modifier and Type | Method and Description
    --- | ---
    `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.
    `protected RealMatrix` | GLSMultipleLinearRegression.`calculateBetaVariance()` Calculates the variance on the beta.
    `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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