Uses of Interface org.apache.commons.math3.linear.RealMatrix (Apache Commons Math 3.3 API)

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

- Packages that use RealMatrix
  Package | Description
  --- | ---
  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.fitting.leastsquares | This package provides algorithms that minimize the residuals between observations and model values.
  org.apache.commons.math3.linear | Linear algebra support.
  org.apache.commons.math3.ml.clustering | Clustering algorithms.
  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
    Modifier and Type | Method and Description
    --- | ---
    `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
    Modifier and Type | Method and Description
    --- | ---
    `RealMatrix` | DefaultProcessModel.`getControlMatrix()` Returns the control matrix.
    `RealMatrix` | ProcessModel.`getControlMatrix()` Returns the control matrix.
    `RealMatrix` | KalmanFilter.`getErrorCovarianceMatrix()` Returns a copy of the current error covariance matrix.
    `RealMatrix` | DefaultProcessModel.`getInitialErrorCovariance()` Returns the initial error covariance matrix.
    `RealMatrix` | ProcessModel.`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` | DefaultProcessModel.`getProcessNoise()` Returns the process noise matrix.
    `RealMatrix` | ProcessModel.`getProcessNoise()` Returns the process noise matrix.
    `RealMatrix` | DefaultProcessModel.`getStateTransitionMatrix()` Returns the state transition matrix.
    `RealMatrix` | ProcessModel.`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.fitting.leastsquares

    Methods in org.apache.commons.math3.fitting.leastsquares that return RealMatrix
    Modifier and Type | Method and Description
    --- | ---
    `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.apache.commons.math3.fitting.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.apache.commons.math3.fitting.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(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.
    `protected abstract RealVector` | GaussNewtonOptimizer.Decomposition.`solve(RealMatrix jacobian, RealVector residuals)` Solve the linear least squares problem Jx=r.
    `LeastSquaresBuilder` | LeastSquaresBuilder.`weight(RealMatrix newWeight)` Configure the weight matrix.
    `static LeastSquaresProblem` | LeastSquaresFactory.`weightMatrix(LeastSquaresProblem problem, RealMatrix weights)` Apply a dense weight matrix to the `LeastSquaresProblem`.

  - ### Uses of RealMatrix in org.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` | `DiagonalMatrix` Implementation of a diagonal 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)` 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` | DiagonalMatrix.`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` | 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` | 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` | 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` | RealMatrix.`createMatrix(int rowDimension, int columnDimension)` Create a new RealMatrix of the same type as the instance with the supplied row and column dimensions.
    `static RealMatrix` | MatrixUtils.`createRealDiagonalMatrix(double[] diagonal)` Returns a diagonal matrix with specified elements.
    `static RealMatrix` | MatrixUtils.`createRealIdentityMatrix(int dimension)` Returns `dimension x dimension` identity matrix.
    `static RealMatrix` | MatrixUtils.`createRealMatrix(double[][] data)` Returns a `RealMatrix` whose entries are the the values in the the input array.
    `static RealMatrix` | MatrixUtils.`createRealMatrix(int rows, int columns)` Returns a `RealMatrix` with specified dimensions.
    `static RealMatrix` | MatrixUtils.`createRowRealMatrix(double[] rowData)` Create a row `RealMatrix` using the data from the input array.
    `RealMatrix` | AbstractRealMatrix.`getColumnMatrix(int column)` Get the entries at the given column index as a column matrix.
    `RealMatrix` | RealMatrix.`getColumnMatrix(int column)` Get the entries at the given column index as a column matrix.
    `RealMatrix` | SingularValueDecomposition.`getCovariance(double minSingularValue)` Returns the n × n covariance matrix.
    `RealMatrix` | EigenDecomposition.`getD()` Gets the block diagonal matrix D of the decomposition.
    `RealMatrix` | QRDecomposition.`getH()` Returns the Householder reflector vectors.
    `RealMatrix` | DecompositionSolver.`getInverse()` Get the pseudo-inverse of the decomposed matrix.
    `RealMatrix` | 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` | RRQRDecomposition.`getP()` Returns the pivot matrix, P, used in the QR Decomposition of matrix A such that AP = QR.
    `RealMatrix` | QRDecomposition.`getQ()` Returns the matrix Q of the decomposition.
    `RealMatrix` | QRDecomposition.`getQT()` Returns the transpose of the matrix Q of the decomposition.
    `RealMatrix` | QRDecomposition.`getR()` Returns the matrix R of the decomposition.
    `RealMatrix` | RectangularCholeskyDecomposition.`getRootMatrix()` Get the root of the covariance matrix.
    `RealMatrix` | AbstractRealMatrix.`getRowMatrix(int row)` Get the entries at the given row index as a row matrix.
    `RealMatrix` | RealMatrix.`getRowMatrix(int row)` Get the entries at the given row index as a row matrix.
    `RealMatrix` | SingularValueDecomposition.`getS()` Returns the diagonal matrix Σ of the decomposition.
    `RealMatrix` | EigenDecomposition.`getSquareRoot()` Computes the square-root of the matrix.
    `RealMatrix` | AbstractRealMatrix.`getSubMatrix(int[] selectedRows, int[] selectedColumns)` Gets a submatrix.
    `RealMatrix` | 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.
    `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` | 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` | 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` | 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` | BlockRealMatrix.`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` | RealMatrix.`scalarMultiply(double d)` Returns the result of multiplying each entry of `this` by `d`.
    `RealMatrix` | DecompositionSolver.`solve(RealMatrix b)` Solve the linear equation A × X = B for matrices A.
    `RealMatrix` | 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
    Modifier and Type | Method and Description
    --- | ---
    `BlockRealMatrix` | BlockRealMatrix.`add(RealMatrix m)` Returns the sum of `this` and `m`.
    `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.
    `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 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` | 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`.
    `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.`multiply(RealMatrix m)` 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` | BlockRealMatrix.`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` | RealMatrix.`setColumnMatrix(int column, RealMatrix matrix)` Sets the specified `column` of `this` matrix to the entries of the specified column `matrix`.
    `void` | BlockRealMatrix.`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` | RealMatrix.`setRowMatrix(int row, RealMatrix matrix)` Sets the specified `row` of `this` matrix to the entries of the specified row `matrix`.
    `RealMatrix` | DecompositionSolver.`solve(RealMatrix b)` Solve the linear equation A × X = B for matrices A.
    `static void` | MatrixUtils.`solveLowerTriangularSystem(RealMatrix rm, RealVector b)` Solve a system of composed of a Lower Triangular Matrix `RealMatrix`.
    `static void` | MatrixUtils.`solveUpperTriangularSystem(RealMatrix rm, RealVector b)` Solver a system composed of an Upper Triangular Matrix `RealMatrix`.
    `OpenMapRealMatrix` | OpenMapRealMatrix.`subtract(RealMatrix m)` Returns `this` minus `m`.
    `BlockRealMatrix` | BlockRealMatrix.`subtract(RealMatrix m)` Returns `this` minus `m`.
    `RealMatrix` | AbstractRealMatrix.`subtract(RealMatrix m)` Returns `this` minus `m`.
    `RealMatrix` | RealMatrix.`subtract(RealMatrix m)` Returns `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)` 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.
    `RRQRDecomposition(RealMatrix matrix)` Calculates the QR-decomposition of the given matrix.
    `RRQRDecomposition(RealMatrix matrix, double threshold)` Calculates the QR-decomposition of the given matrix.
    `SingularValueDecomposition(RealMatrix matrix)` Calculates the compact Singular Value Decomposition of the given matrix.

  - ### Uses of RealMatrix in org.apache.commons.math3.ml.clustering

    Methods in org.apache.commons.math3.ml.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.apache.commons.math3.optim.nonlinear.scalar

    Constructors in org.apache.commons.math3.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.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
    Modifier and Type | Method and Description
    --- | ---
    `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
    Modifier and Type | Method and Description
    --- | ---
    `RealMatrix` | Weight.`getWeight()` Deprecated. Gets the initial guess.
    `RealMatrix` | MultivariateVectorOptimizer.`getWeight()` Gets the weight matrix of the observations.

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

  - ### 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
    Modifier and Type | Method and Description
    --- | ---
    `protected RealMatrix` | AbstractLeastSquaresOptimizer.`computeWeightedJacobian(double[] params)` Deprecated. Computes the weighted Jacobian matrix.
    `RealMatrix` | AbstractLeastSquaresOptimizer.`getWeightSquareRoot()` Deprecated. 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
    Modifier and Type | Method and Description
    --- | ---
    `RealMatrix` | Weight.`getWeight()` Deprecated. Gets the initial guess.

    Constructors in org.apache.commons.math3.optimization with parameters of type RealMatrix
    Constructor and Description
    `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
    Modifier and Type | Method and Description
    --- | ---
    `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
    Modifier and Type | Method and Description
    --- | ---
    `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
    Modifier and Type | Method and Description
    --- | ---
    `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
    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` | 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.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` | 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.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.
    `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.apache.commons.math3.stat.descriptive

    Methods in org.apache.commons.math3.stat.descriptive that return RealMatrix
    Modifier and Type | Method and Description
    --- | ---
    `RealMatrix` | MultivariateSummaryStatistics.`getCovariance()` Returns the covariance matrix of the values that have been added.
    `RealMatrix` | StatisticalMultivariateSummary.`getCovariance()` Returns the covariance of the available values.
    `RealMatrix` | SynchronizedMultivariateSummaryStatistics.`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 abstract RealMatrix` | AbstractMultipleLinearRegression.`calculateBetaVariance()` Calculates the beta variance of multiple linear regression in matrix notation.
    `protected RealMatrix` | OLSMultipleLinearRegression.`calculateBetaVariance()` Calculates the variance-covariance matrix of the regression parameters.
    `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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