Uses of Interface
org.apache.commons.math3.linear.RealMatrix
Packages that use RealMatrix
Package
Description
Implementations of common discrete and continuous distributions.
Implementations of common discrete-time linear filters.
This package provides algorithms that minimize the residuals
between observations and model values.
Linear algebra support.
Clustering algorithms.
Algorithms for optimizing a scalar function.
This package provides optimization algorithms that do not require derivatives.
Algorithms for optimizing a vector function.
This package provides optimization algorithms that require derivatives.
All classes and sub-packages of this package are deprecated.
This package provides optimization algorithms that don't require derivatives.
This package provides optimization algorithms that require derivatives.
Random number and random data generators.
Correlations/Covariance computations.
Generic univariate summary statistic objects.
Summary statistics based on moments.
Statistical routines involving multivariate data.
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Uses of RealMatrix in org.apache.commons.math3.distribution
Methods in org.apache.commons.math3.distribution that return RealMatrixModifier and TypeMethodDescriptionMultivariateNormalDistribution.getCovariances()Gets the covariance matrix. -
Uses of RealMatrix in org.apache.commons.math3.filter
Methods in org.apache.commons.math3.filter that return RealMatrixModifier and TypeMethodDescriptionDefaultProcessModel.getControlMatrix()Returns the control matrix.ProcessModel.getControlMatrix()Returns the control matrix.KalmanFilter.getErrorCovarianceMatrix()Returns a copy of the current error covariance matrix.DefaultProcessModel.getInitialErrorCovariance()Returns the initial error covariance matrix.ProcessModel.getInitialErrorCovariance()Returns the initial error covariance matrix.DefaultMeasurementModel.getMeasurementMatrix()Returns the measurement matrix.MeasurementModel.getMeasurementMatrix()Returns the measurement matrix.DefaultMeasurementModel.getMeasurementNoise()Returns the measurement noise matrix.MeasurementModel.getMeasurementNoise()Returns the measurement noise matrix.DefaultProcessModel.getProcessNoise()Returns the process noise matrix.ProcessModel.getProcessNoise()Returns the process noise matrix.DefaultProcessModel.getStateTransitionMatrix()Returns the state transition matrix.ProcessModel.getStateTransitionMatrix()Returns the state transition matrix.Constructors in org.apache.commons.math3.filter with parameters of type RealMatrixModifierConstructorDescriptionDefaultMeasurementModel(RealMatrix measMatrix, RealMatrix measNoise) Create a newMeasurementModel, takingRealMatrixobjects as input parameters for the respective measurement matrix and noise.DefaultProcessModel(RealMatrix stateTransition, RealMatrix control, RealMatrix processNoise, RealVector initialStateEstimate, RealMatrix initialErrorCovariance) Create a newProcessModel, 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 RealMatrixModifier and TypeMethodDescriptionValueAndJacobianFunction.computeJacobian(double[] params) Compute the Jacobian.AbstractEvaluation.getCovariances(double threshold) Get the covariance matrix of the optimized parameters.LeastSquaresProblem.Evaluation.getCovariances(double threshold) Get the covariance matrix of the optimized parameters.LeastSquaresProblem.Evaluation.getJacobian()Get the weighted Jacobian matrix.Methods in org.apache.commons.math3.fitting.leastsquares that return types with arguments of type RealMatrixModifier and TypeMethodDescriptionMultivariateJacobianFunction.value(RealVector point) Compute the function value and its Jacobian.Methods in org.apache.commons.math3.fitting.leastsquares with parameters of type RealMatrixModifier and TypeMethodDescriptionstatic LeastSquaresProblemLeastSquaresFactory.create(MultivariateVectorFunction model, MultivariateMatrixFunction jacobian, double[] observed, double[] start, RealMatrix weight, ConvergenceChecker<LeastSquaresProblem.Evaluation> checker, int maxEvaluations, int maxIterations) Create aLeastSquaresProblemfrom the given elements.static LeastSquaresProblemLeastSquaresFactory.create(MultivariateJacobianFunction model, RealVector observed, RealVector start, RealMatrix weight, ConvergenceChecker<LeastSquaresProblem.Evaluation> checker, int maxEvaluations, int maxIterations) Create aLeastSquaresProblemfrom the given elements.static LeastSquaresProblemLeastSquaresFactory.create(MultivariateJacobianFunction model, RealVector observed, RealVector start, RealMatrix weight, ConvergenceChecker<LeastSquaresProblem.Evaluation> checker, int maxEvaluations, int maxIterations, boolean lazyEvaluation, ParameterValidator paramValidator) Create aLeastSquaresProblemfrom the given elements.protected abstract RealVectorGaussNewtonOptimizer.Decomposition.solve(RealMatrix jacobian, RealVector residuals) Solve the linear least squares problem Jx=r.LeastSquaresBuilder.weight(RealMatrix newWeight) Configure the weight matrix.static LeastSquaresProblemLeastSquaresFactory.weightMatrix(LeastSquaresProblem problem, RealMatrix weights) Apply a dense weight matrix to theLeastSquaresProblem. -
Uses of RealMatrix in org.apache.commons.math3.linear
Subinterfaces of RealMatrix in org.apache.commons.math3.linearModifier and TypeInterfaceDescriptioninterfaceMarker interface forRealMatriximplementations that require sparse backing storageClasses in org.apache.commons.math3.linear that implement RealMatrixModifier and TypeClassDescriptionclassBasic implementation of RealMatrix methods regardless of the underlying storage.classImplementation ofRealMatrixusing adouble[][]array to store entries.classCache-friendly implementation of RealMatrix using a flat arrays to store square blocks of the matrix.classImplementation of a diagonal matrix.classSparse matrix implementation based on an open addressed map.Methods in org.apache.commons.math3.linear that return RealMatrixModifier and TypeMethodDescriptionAbstractRealMatrix.add(RealMatrix m) Returns the sum ofthisandm.RealMatrix.add(RealMatrix m) Returns the sum ofthisandm.static RealMatrixMatrixUtils.blockInverse(RealMatrix m, int splitIndex) Computes the inverse of the given matrix by splitting it into 4 sub-matrices.abstract RealMatrixAbstractRealMatrix.copy()Returns a (deep) copy of this.Array2DRowRealMatrix.copy()Returns a (deep) copy of this.DiagonalMatrix.copy()Returns a (deep) copy of this.RealMatrix.copy()Returns a (deep) copy of this.static RealMatrixMatrixUtils.createColumnRealMatrix(double[] columnData) Creates a columnRealMatrixusing the data from the input array.abstract RealMatrixAbstractRealMatrix.createMatrix(int rowDimension, int columnDimension) Create a new RealMatrix of the same type as the instance with the supplied row and column dimensions.Array2DRowRealMatrix.createMatrix(int rowDimension, int columnDimension) Create a new RealMatrix of the same type as the instance with the supplied row and column dimensions.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.createMatrix(int rowDimension, int columnDimension) Create a new RealMatrix of the same type as the instance with the supplied row and column dimensions.static RealMatrixMatrixUtils.createRealDiagonalMatrix(double[] diagonal) Returns a diagonal matrix with specified elements.static RealMatrixMatrixUtils.createRealIdentityMatrix(int dimension) Returnsdimension x dimensionidentity matrix.static RealMatrixMatrixUtils.createRealMatrix(double[][] data) Returns aRealMatrixwhose entries are the the values in the the input array.static RealMatrixMatrixUtils.createRealMatrix(int rows, int columns) Returns aRealMatrixwith specified dimensions.static RealMatrixMatrixUtils.createRowRealMatrix(double[] rowData) Create a rowRealMatrixusing the data from the input array.AbstractRealMatrix.getColumnMatrix(int column) Get the entries at the given column index as a column matrix.RealMatrix.getColumnMatrix(int column) Get the entries at the given column index as a column matrix.SingularValueDecomposition.getCovariance(double minSingularValue) Returns the n × n covariance matrix.EigenDecomposition.getD()Gets the block diagonal matrix D of the decomposition.QRDecomposition.getH()Returns the Householder reflector vectors.DecompositionSolver.getInverse()Get the pseudo-inverse of the decomposed matrix.CholeskyDecomposition.getL()Returns the matrix L of the decomposition.LUDecomposition.getL()Returns the matrix L of the decomposition.CholeskyDecomposition.getLT()Returns the transpose of the matrix L of the decomposition.LUDecomposition.getP()Returns the P rows permutation matrix.RRQRDecomposition.getP()Returns the pivot matrix, P, used in the QR Decomposition of matrix A such that AP = QR.QRDecomposition.getQ()Returns the matrix Q of the decomposition.QRDecomposition.getQT()Returns the transpose of the matrix Q of the decomposition.QRDecomposition.getR()Returns the matrix R of the decomposition.RectangularCholeskyDecomposition.getRootMatrix()Get the root of the covariance matrix.AbstractRealMatrix.getRowMatrix(int row) Get the entries at the given row index as a row matrix.RealMatrix.getRowMatrix(int row) Get the entries at the given row index as a row matrix.SingularValueDecomposition.getS()Returns the diagonal matrix Σ of the decomposition.EigenDecomposition.getSquareRoot()Computes the square-root of the matrix.AbstractRealMatrix.getSubMatrix(int[] selectedRows, int[] selectedColumns) Gets a submatrix.AbstractRealMatrix.getSubMatrix(int startRow, int endRow, int startColumn, int endColumn) Gets a submatrix.RealMatrix.getSubMatrix(int[] selectedRows, int[] selectedColumns) Gets a submatrix.RealMatrix.getSubMatrix(int startRow, int endRow, int startColumn, int endColumn) Gets a submatrix.LUDecomposition.getU()Returns the matrix U of the decomposition.SingularValueDecomposition.getU()Returns the matrix U of the decomposition.SingularValueDecomposition.getUT()Returns the transpose of the matrix U of the decomposition.EigenDecomposition.getV()Gets the matrix V of the decomposition.SingularValueDecomposition.getV()Returns the matrix V of the decomposition.EigenDecomposition.getVT()Gets the transpose of the matrix V of the decomposition.SingularValueDecomposition.getVT()Returns the transpose of the matrix V of the decomposition.static RealMatrixMatrixUtils.inverse(RealMatrix matrix) Computes the inverse of the given matrix.static RealMatrixMatrixUtils.inverse(RealMatrix matrix, double threshold) Computes the inverse of the given matrix.AbstractRealMatrix.multiply(RealMatrix m) Returns the result of postmultiplyingthisbym.DiagonalMatrix.multiply(RealMatrix m) Returns the result of postmultiplyingthisbym.OpenMapRealMatrix.multiply(RealMatrix m) Returns the result of postmultiplyingthisbym.RealMatrix.multiply(RealMatrix m) Returns the result of postmultiplyingthisbym.ArrayRealVector.outerProduct(RealVector v) Compute the outer product.RealVector.outerProduct(RealVector v) Compute the outer product.Parse a string to produce aRealMatrixobject.RealMatrixFormat.parse(String source, ParsePosition pos) Parse a string to produce aRealMatrixobject.AbstractRealMatrix.power(int p) Returns the result of multiplyingthiswith itselfptimes.RealMatrix.power(int p) Returns the result of multiplyingthiswith itselfptimes.AbstractRealMatrix.preMultiply(RealMatrix m) Returns the result of premultiplyingthisbym.RealMatrix.preMultiply(RealMatrix m) Returns the result of premultiplyingthisbym.AbstractRealMatrix.scalarAdd(double d) Returns the result of addingdto each entry ofthis.RealMatrix.scalarAdd(double d) Returns the result of addingdto each entry ofthis.AbstractRealMatrix.scalarMultiply(double d) Returns the result of multiplying each entry ofthisbyd.BlockRealMatrix.scalarMultiply(double d) Returns the result of multiplying each entry ofthisbyd.RealMatrix.scalarMultiply(double d) Returns the result of multiplying each entry ofthisbyd.DecompositionSolver.solve(RealMatrix b) Solve the linear equation A × X = B for matrices A.AbstractRealMatrix.subtract(RealMatrix m) Returnsthisminusm.RealMatrix.subtract(RealMatrix m) Returnsthisminusm.AbstractRealMatrix.transpose()Returns the transpose of this matrix.RealMatrix.transpose()Returns the transpose of this matrix.Methods in org.apache.commons.math3.linear with parameters of type RealMatrixModifier and TypeMethodDescriptionAbstractRealMatrix.add(RealMatrix m) Returns the sum ofthisandm.BlockRealMatrix.add(RealMatrix m) Returns the sum ofthisandm.RealMatrix.add(RealMatrix m) Returns the sum ofthisandm.static RealMatrixMatrixUtils.blockInverse(RealMatrix m, int splitIndex) Computes the inverse of the given matrix by splitting it into 4 sub-matrices.static voidMatrixUtils.checkSymmetric(RealMatrix matrix, double eps) Checks whether a matrix is symmetric.RealMatrixFormat.format(RealMatrix m) This method callsRealMatrixFormat.format(RealMatrix,StringBuffer,FieldPosition).RealMatrixFormat.format(RealMatrix matrix, StringBuffer toAppendTo, FieldPosition pos) Formats aRealMatrixobject to produce a string.static RealMatrixMatrixUtils.inverse(RealMatrix matrix) Computes the inverse of the given matrix.static RealMatrixMatrixUtils.inverse(RealMatrix matrix, double threshold) Computes the inverse of the given matrix.static booleanMatrixUtils.isSymmetric(RealMatrix matrix, double eps) Checks whether a matrix is symmetric.AbstractRealMatrix.multiply(RealMatrix m) Returns the result of postmultiplyingthisbym.BlockRealMatrix.multiply(RealMatrix m) Returns the result of postmultiplyingthisbym.DiagonalMatrix.multiply(RealMatrix m) Returns the result of postmultiplyingthisbym.OpenMapRealMatrix.multiply(RealMatrix m) Returns the result of postmultiplyingthisbym.RealMatrix.multiply(RealMatrix m) Returns the result of postmultiplyingthisbym.AbstractRealMatrix.preMultiply(RealMatrix m) Returns the result of premultiplyingthisbym.RealMatrix.preMultiply(RealMatrix m) Returns the result of premultiplyingthisbym.static voidMatrixUtils.serializeRealMatrix(RealMatrix matrix, ObjectOutputStream oos) Serialize aRealMatrix.voidAbstractRealMatrix.setColumnMatrix(int column, RealMatrix matrix) Sets the specifiedcolumnofthismatrix to the entries of the specified columnmatrix.voidBlockRealMatrix.setColumnMatrix(int column, RealMatrix matrix) Sets the specifiedcolumnofthismatrix to the entries of the specified columnmatrix.voidRealMatrix.setColumnMatrix(int column, RealMatrix matrix) Sets the specifiedcolumnofthismatrix to the entries of the specified columnmatrix.voidAbstractRealMatrix.setRowMatrix(int row, RealMatrix matrix) Sets the specifiedrowofthismatrix to the entries of the specified rowmatrix.voidBlockRealMatrix.setRowMatrix(int row, RealMatrix matrix) Sets the specifiedrowofthismatrix to the entries of the specified rowmatrix.voidRealMatrix.setRowMatrix(int row, RealMatrix matrix) Sets the specifiedrowofthismatrix to the entries of the specified rowmatrix.DecompositionSolver.solve(RealMatrix b) Solve the linear equation A × X = B for matrices A.static voidMatrixUtils.solveLowerTriangularSystem(RealMatrix rm, RealVector b) Solve a system of composed of a Lower Triangular MatrixRealMatrix.static voidMatrixUtils.solveUpperTriangularSystem(RealMatrix rm, RealVector b) Solver a system composed of an Upper Triangular MatrixRealMatrix.AbstractRealMatrix.subtract(RealMatrix m) Returnsthisminusm.BlockRealMatrix.subtract(RealMatrix m) Returnsthisminusm.OpenMapRealMatrix.subtract(RealMatrix m) Returnsthisminusm.RealMatrix.subtract(RealMatrix m) Returnsthisminusm.Constructors in org.apache.commons.math3.linear with parameters of type RealMatrixModifierConstructorDescriptionCholeskyDecomposition(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 parameterLUDecomposition(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.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 RealMatrixModifier and TypeMethodDescriptionFuzzyKMeansClusterer.getMembershipMatrix()Returns thenxkmembership matrix, wherenis the number of data points andkthe 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 RealMatrixModifierConstructorDescriptionLeastSquaresConverter(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 RealMatrixModifier and TypeMethodDescriptionCMAESOptimizer.getStatisticsDHistory()CMAESOptimizer.getStatisticsMeanHistory() -
Uses of RealMatrix in org.apache.commons.math3.optim.nonlinear.vector
Methods in org.apache.commons.math3.optim.nonlinear.vector that return RealMatrixModifier and TypeMethodDescriptionMultivariateVectorOptimizer.getWeight()Deprecated.Gets the weight matrix of the observations.Weight.getWeight()Deprecated.Gets the initial guess.Constructors in org.apache.commons.math3.optim.nonlinear.vector with parameters of type RealMatrix -
Uses of RealMatrix in org.apache.commons.math3.optim.nonlinear.vector.jacobian
Methods in org.apache.commons.math3.optim.nonlinear.vector.jacobian that return RealMatrixModifier and TypeMethodDescriptionprotected RealMatrixAbstractLeastSquaresOptimizer.computeWeightedJacobian(double[] params) Deprecated.Computes the weighted Jacobian matrix.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 RealMatrixConstructors in org.apache.commons.math3.optimization with parameters of type RealMatrixModifierConstructorDescriptionLeastSquaresConverter(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 RealMatrixModifier and TypeMethodDescriptionBaseAbstractMultivariateVectorOptimizer.getWeight()Deprecated.Gets the weight matrix of the observations.Methods in org.apache.commons.math3.optimization.direct that return types with arguments of type RealMatrixModifier and TypeMethodDescriptionCMAESOptimizer.getStatisticsDHistory()Deprecated.CMAESOptimizer.getStatisticsMeanHistory()Deprecated. -
Uses of RealMatrix in org.apache.commons.math3.optimization.general
Methods in org.apache.commons.math3.optimization.general that return RealMatrixModifier and TypeMethodDescriptionprotected RealMatrixAbstractLeastSquaresOptimizer.computeWeightedJacobian(double[] params) Deprecated.Computes the Jacobian matrix.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 RealMatrixModifier and TypeMethodDescriptionCorrelatedRandomVectorGenerator.getRootMatrix()Get the root of the covariance matrix.Constructors in org.apache.commons.math3.random with parameters of type RealMatrixModifierConstructorDescriptionCorrelatedRandomVectorGenerator(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 RealMatrixModifier and TypeMethodDescriptionKendallsCorrelation.computeCorrelationMatrix(double[][] matrix) Computes the Kendall's Tau rank correlation matrix for the columns of the input rectangular array.KendallsCorrelation.computeCorrelationMatrix(RealMatrix matrix) Computes the Kendall's Tau rank correlation matrix for the columns of the input matrix.PearsonsCorrelation.computeCorrelationMatrix(double[][] data) Computes the correlation matrix for the columns of the input rectangular array.PearsonsCorrelation.computeCorrelationMatrix(RealMatrix matrix) Computes the correlation matrix for the columns of the input matrix, usingPearsonsCorrelation.correlation(double[], double[]).SpearmansCorrelation.computeCorrelationMatrix(double[][] matrix) Computes the Spearman's rank correlation matrix for the columns of the input rectangular array.SpearmansCorrelation.computeCorrelationMatrix(RealMatrix matrix) Computes the Spearman's rank correlation matrix for the columns of the input matrix.protected RealMatrixCovariance.computeCovarianceMatrix(double[][] data) Create a covariance matrix from a rectangular array whose columns represent covariates.protected RealMatrixCovariance.computeCovarianceMatrix(double[][] data, boolean biasCorrected) Compute a covariance matrix from a rectangular array whose columns represent covariates.protected RealMatrixCovariance.computeCovarianceMatrix(RealMatrix matrix) Create a covariance matrix from a matrix whose columns represent covariates.protected RealMatrixCovariance.computeCovarianceMatrix(RealMatrix matrix, boolean biasCorrected) Compute a covariance matrix from a matrix whose columns represent covariates.PearsonsCorrelation.covarianceToCorrelation(RealMatrix covarianceMatrix) Derives a correlation matrix from a covariance matrix.KendallsCorrelation.getCorrelationMatrix()Returns the correlation matrix.PearsonsCorrelation.getCorrelationMatrix()Returns the correlation matrix.SpearmansCorrelation.getCorrelationMatrix()Calculate the Spearman Rank Correlation Matrix.PearsonsCorrelation.getCorrelationPValues()Returns a matrix of p-values associated with the (two-sided) null hypothesis that the corresponding correlation coefficient is zero.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 withgetCorrelationMatrix.getEntry(i,j)Covariance.getCovarianceMatrix()Returns the covariance matrixStorelessCovariance.getCovarianceMatrix()Returns the covariance matrixMethods in org.apache.commons.math3.stat.correlation with parameters of type RealMatrixModifier and TypeMethodDescriptionKendallsCorrelation.computeCorrelationMatrix(RealMatrix matrix) Computes the Kendall's Tau rank correlation matrix for the columns of the input matrix.PearsonsCorrelation.computeCorrelationMatrix(RealMatrix matrix) Computes the correlation matrix for the columns of the input matrix, usingPearsonsCorrelation.correlation(double[], double[]).SpearmansCorrelation.computeCorrelationMatrix(RealMatrix matrix) Computes the Spearman's rank correlation matrix for the columns of the input matrix.protected RealMatrixCovariance.computeCovarianceMatrix(RealMatrix matrix) Create a covariance matrix from a matrix whose columns represent covariates.protected RealMatrixCovariance.computeCovarianceMatrix(RealMatrix matrix, boolean biasCorrected) Compute a covariance matrix from a matrix whose columns represent covariates.PearsonsCorrelation.covarianceToCorrelation(RealMatrix covarianceMatrix) Derives a correlation matrix from a covariance matrix.Constructors in org.apache.commons.math3.stat.correlation with parameters of type RealMatrixModifierConstructorDescriptionCovariance(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 RealMatrixModifier and TypeMethodDescriptionMultivariateSummaryStatistics.getCovariance()Returns the covariance matrix of the values that have been added.StatisticalMultivariateSummary.getCovariance()Returns the covariance of the available values.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 -
Uses of RealMatrix in org.apache.commons.math3.stat.regression
Methods in org.apache.commons.math3.stat.regression that return RealMatrixModifier and TypeMethodDescriptionprotected abstract RealMatrixAbstractMultipleLinearRegression.calculateBetaVariance()Calculates the beta variance of multiple linear regression in matrix notation.protected RealMatrixGLSMultipleLinearRegression.calculateBetaVariance()Calculates the variance on the beta.protected RealMatrixOLSMultipleLinearRegression.calculateBetaVariance()Calculates the variance-covariance matrix of the regression parameters.OLSMultipleLinearRegression.calculateHat()Compute the "hat" matrix.protected RealMatrixGLSMultipleLinearRegression.getOmegaInverse()Get the inverse of the covariance.protected RealMatrixAbstractMultipleLinearRegression.getX()