# 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
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
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`
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`
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
Modifier
Constructor
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
Description
`RealMatrix`
ValueAndJacobianFunction.`computeJacobian(double[] params)`
Compute the Jacobian.
`RealMatrix`
AbstractEvaluation.`getCovariances(double threshold)`
Get the covariance matrix of the optimized parameters.
`RealMatrix`
LeastSquaresProblem.Evaluation.`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
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
Description
`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.
`static LeastSquaresProblem`
LeastSquaresFactory.`create(MultivariateJacobianFunction model, RealVector observed, RealVector start, RealMatrix weight, ConvergenceChecker<LeastSquaresProblem.Evaluation> checker, int maxEvaluations, int maxIterations)`
Create a `LeastSquaresProblem` from the given elements.
`static LeastSquaresProblem`
LeastSquaresFactory.`create(MultivariateJacobianFunction model, RealVector observed, RealVector start, RealMatrix weight, ConvergenceChecker<LeastSquaresProblem.Evaluation> checker, int maxEvaluations, int maxIterations, boolean lazyEvaluation, ParameterValidator paramValidator)`
Create a `LeastSquaresProblem` from the given elements.
`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
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
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
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.
`abstract RealMatrix`
AbstractRealMatrix.`copy()`
Returns a (deep) copy of this.
`RealMatrix`
Array2DRowRealMatrix.`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.
`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`
Array2DRowRealMatrix.`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 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`
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`
AbstractRealMatrix.`getSubMatrix(int startRow, int endRow, int startColumn, int endColumn)`
Gets a submatrix.
`RealMatrix`
RealMatrix.`getSubMatrix(int[] selectedRows, int[] selectedColumns)`
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`
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.
`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`
AbstractRealMatrix.`multiply(RealMatrix m)`
Returns the result of postmultiplying `this` by `m`.
`RealMatrix`
DiagonalMatrix.`multiply(RealMatrix m)`
Returns the result of postmultiplying `this` by `m`.
`RealMatrix`
OpenMapRealMatrix.`multiply(RealMatrix m)`
Returns the result of postmultiplying `this` by `m`.
`RealMatrix`
RealMatrix.`multiply(RealMatrix m)`
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`
BlockRealMatrix.`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
Description
`RealMatrix`
AbstractRealMatrix.`add(RealMatrix m)`
Returns the sum of `this` and `m`.
`BlockRealMatrix`
BlockRealMatrix.`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`
AbstractRealMatrix.`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`
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`
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`
AbstractRealMatrix.`setColumnMatrix(int column, RealMatrix matrix)`
Sets the specified `column` of `this` matrix to the entries of the specified column `matrix`.
`void`
BlockRealMatrix.`setColumnMatrix(int column, RealMatrix matrix)`
Sets the specified `column` of `this` matrix to the entries of the specified column `matrix`.
`void`
RealMatrix.`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`
BlockRealMatrix.`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`.
`RealMatrix`
AbstractRealMatrix.`subtract(RealMatrix m)`
Returns `this` minus `m`.
`BlockRealMatrix`
BlockRealMatrix.`subtract(RealMatrix m)`
Returns `this` minus `m`.
`OpenMapRealMatrix`
OpenMapRealMatrix.`subtract(RealMatrix m)`
Returns `this` minus `m`.
`RealMatrix`
RealMatrix.`subtract(RealMatrix m)`
Returns `this` minus `m`.
Constructors in org.apache.commons.math3.linear with parameters of type RealMatrix
Modifier
Constructor
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
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
Modifier
Constructor
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
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
Description
`RealMatrix`
MultivariateVectorOptimizer.`getWeight()`
Deprecated.
Gets the weight matrix of the observations.
`RealMatrix`
Weight.`getWeight()`
Deprecated.
Gets the initial guess.
Constructors in org.apache.commons.math3.optim.nonlinear.vector with parameters of type RealMatrix
Modifier
Constructor
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
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
Description
`RealMatrix`
Weight.`getWeight()`
Deprecated.
Gets the initial guess.
Constructors in org.apache.commons.math3.optimization with parameters of type RealMatrix
Modifier
Constructor
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
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
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
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
Description
`RealMatrix`
CorrelatedRandomVectorGenerator.`getRootMatrix()`
Get the root of the covariance matrix.
Constructors in org.apache.commons.math3.random with parameters of type RealMatrix
Modifier
Constructor
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
Description
`RealMatrix`
KendallsCorrelation.`computeCorrelationMatrix(double[][] matrix)`
Computes the Kendall's Tau rank correlation matrix for the columns of the input rectangular array.
`RealMatrix`
KendallsCorrelation.`computeCorrelationMatrix(RealMatrix matrix)`
Computes the Kendall's Tau rank correlation matrix for the columns of the input matrix.
`RealMatrix`
PearsonsCorrelation.`computeCorrelationMatrix(double[][] data)`
Computes the 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, using `PearsonsCorrelation.correlation(double[], double[])`.
`RealMatrix`
SpearmansCorrelation.`computeCorrelationMatrix(double[][] matrix)`
Computes the Spearman's rank 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.
`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`
KendallsCorrelation.`getCorrelationMatrix()`
Returns the correlation 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`
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
Description
`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[])`.
`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
Modifier
Constructor
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
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
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
Description
`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()`