Uses of Interface
org.hipparchus.linear.RealMatrix
Package
Description
Clustering algorithms.
Implementations of multivariate distributions.
Kalman filter.
Kalman filter implementation for non-linear processes.
Kalman filter implementation for linear processes.
Unscented Kalman filter implementation.
Linear algebra support.
This package provides classes to solve non-stiff Ordinary Differential Equations problems.
Algorithms for optimizing a scalar function.
This package provides optimization algorithms that do not require derivatives.
This package provides algorithms that minimize the residuals
between observations and model values.
This package provides algorithms that minimize the residuals
between observations and model values.
Random number and random data generators.
Correlations/Covariance computations.
Generic univariate and multivariate summary statistic objects.
Multivariate statistics.
Statistical routines involving multivariate data.
Convenience routines and common data structures used throughout the Hipparchus library.
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Uses of RealMatrix in org.hipparchus.clustering
Modifier and TypeMethodDescriptionFuzzyKMeansClusterer.getMembershipMatrix()
Returns thenxk
membership matrix, wheren
is the number of data points andk
the number of clusters. -
Uses of RealMatrix in org.hipparchus.distribution.multivariate
Modifier and TypeMethodDescriptionMultivariateNormalDistribution.getCovariances()
Gets the covariance matrix. -
Uses of RealMatrix in org.hipparchus.filtering.kalman
Modifier and TypeMethodDescriptionprotected RealMatrix
AbstractKalmanFilter.computeInnovationCovarianceMatrix
(RealMatrix r, RealMatrix h) Compute innovation covariance matrix.Measurement.getCovariance()
Get the measurement covariance.ProcessEstimate.getCovariance()
Get the state covariance.ProcessEstimate.getInnovationCovariance()
Get the innovation covariance matrix.ProcessEstimate.getKalmanGain()
Get the Kalman gain matrix.ProcessEstimate.getMeasurementJacobian()
Get the Jacobian of the measurement with respect to the state (H matrix).ProcessEstimate.getStateTransitionMatrix()
Get state transition matrix between previous state and estimated (but not yet corrected) state.Modifier and TypeMethodDescriptionprotected RealMatrix
AbstractKalmanFilter.computeInnovationCovarianceMatrix
(RealMatrix r, RealMatrix h) Compute innovation covariance matrix.protected void
AbstractKalmanFilter.correct
(T measurement, RealMatrix stm, RealVector innovation, RealMatrix h, RealMatrix s) Perform correction step.protected void
AbstractKalmanFilter.predict
(double time, RealVector predictedState, RealMatrix stm, RealMatrix noise) Perform prediction step.ModifierConstructorDescriptionProcessEstimate
(double time, RealVector state, RealMatrix covariance) Simple constructor.ProcessEstimate
(double time, RealVector state, RealMatrix covariance, RealMatrix stateTransitionMatrix, RealMatrix measurementJacobian, RealMatrix innovationCovariance, RealMatrix kalmanGain) Simple constructor. -
Uses of RealMatrix in org.hipparchus.filtering.kalman.extended
Modifier and TypeMethodDescriptionNonLinearEvolution.getMeasurementJacobian()
Get measurement Jacobian.NonLinearEvolution.getProcessNoiseMatrix()
Get process noise.NonLinearEvolution.getStateTransitionMatrix()
Get state transition matrix between previous and current state.Modifier and TypeMethodDescriptionNonLinearProcess.getInnovation
(T measurement, NonLinearEvolution evolution, RealMatrix innovationCovarianceMatrix) Get the innovation brought by a measurement.ModifierConstructorDescriptionNonLinearEvolution
(double currentTime, RealVector currentState, RealMatrix stateTransitionMatrix, RealMatrix processNoiseMatrix, RealMatrix measurementJacobian) Simple constructor. -
Uses of RealMatrix in org.hipparchus.filtering.kalman.linear
Modifier and TypeMethodDescriptionLinearEvolution.getControlMatrix()
Get the control matrix Bk-1.LinearEvolution.getMeasurementJacobian()
Get measurement Jacobian.LinearEvolution.getProcessNoiseMatrix()
Get the process noise matrix Qk-1.LinearEvolution.getStateTransitionMatrix()
Get the state transition matrix Ak-1.ModifierConstructorDescriptionLinearEvolution
(RealMatrix stateTransitionMatrix, RealMatrix controlMatrix, RealVector command, RealMatrix processNoiseMatrix, RealMatrix measurementJacobian) Simple constructor. -
Uses of RealMatrix in org.hipparchus.filtering.kalman.unscented
Modifier and TypeMethodDescriptionUnscentedProcess.getInnovation
(T measurement, RealVector predictedMeasurement, RealVector predictedState, RealMatrix innovationCovarianceMatrix) Get the innovation brought by a measurement.ModifierConstructorDescriptionUnscentedEvolution
(double currentTime, RealVector[] currentStates, RealMatrix processNoiseMatrix) Constructor. -
Uses of RealMatrix in org.hipparchus.linear
Modifier and TypeInterfaceDescriptioninterface
Marker interface forRealMatrix
implementations that require sparse backing storageModifier and TypeClassDescriptionclass
Basic implementation of RealMatrix methods regardless of the underlying storage.class
Implementation ofRealMatrix
using adouble[][]
array to store entries.class
Cache-friendly implementation of RealMatrix using a flat arrays to store square blocks of the matrix.class
Implementation of a diagonal matrix.class
Sparse matrix implementation based on an open addressed map.Modifier and TypeMethodDescriptionAbstractRealMatrix.add
(RealMatrix m) Returns the sum ofthis
andm
.RealMatrix.add
(RealMatrix m) Returns the sum ofthis
andm
.default RealMatrix
RealMatrix.blendArithmeticallyWith
(RealMatrix other, double blendingValue) Blend arithmetically this instance with another one.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.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 RealMatrix
MatrixUtils.createColumnRealMatrix
(double[] columnData) Creates a columnRealMatrix
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.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 RealMatrix
MatrixUtils.createRealDiagonalMatrix
(double[] diagonal) Returns a diagonal matrix with specified elements.static RealMatrix
MatrixUtils.createRealIdentityMatrix
(int dimension) Returnsdimension x dimension
identity matrix.static RealMatrix
MatrixUtils.createRealMatrix
(double[][] data) Returns aRealMatrix
whose entries are the the values in the the input array.static RealMatrix
MatrixUtils.createRealMatrix
(int rows, int columns) Returns aRealMatrix
with specified dimensions.static RealMatrix
MatrixUtils.createRowRealMatrix
(double[] rowData) Create a rowRealMatrix
using 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.EigenDecompositionNonSymmetric.getD()
Gets the block diagonal matrix D of the decomposition.HessenbergTransformer.getH()
Returns the Hessenberg matrix H of the transform.QRDecomposition.getH()
Returns the Householder reflector vectors.DecompositionSolver.getInverse()
Get the pseudo-inverse of the decomposed matrix.RiccatiEquationSolver.getK()
Get the linear controller k.RiccatiEquationSolverImpl.getK()
{inheritDoc}CholeskyDecomposition.getL()
Returns the matrix L of the decomposition.LUDecomposition.getL()
Returns the matrix L of the decomposition.SemiDefinitePositiveCholeskyDecomposition.getL()
Returns the matrix L of the decomposition.CholeskyDecomposition.getLT()
Returns the transpose of the matrix L of the decomposition.SemiDefinitePositiveCholeskyDecomposition.getLT()
Returns the transpose of the matrix L of the decomposition.HessenbergTransformer.getP()
Returns the matrix P of the transform.LUDecomposition.getP()
Returns the P rows permutation matrix.RiccatiEquationSolver.getP()
Get the solution.RiccatiEquationSolverImpl.getP()
{inheritDoc}RRQRDecomposition.getP()
Returns the pivot matrix, P, used in the QR Decomposition of matrix A such that AP = QR.SchurTransformer.getP()
Returns the matrix P of the transform.HessenbergTransformer.getPT()
Returns the transpose of the matrix P of the transform.SchurTransformer.getPT()
Returns the transpose of the matrix P of the transform.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.EigenDecompositionSymmetric.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.Array2DRowRealMatrix.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.SchurTransformer.getT()
Returns the quasi-triangular Schur matrix T of the transform.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.EigenDecompositionNonSymmetric.getV()
Gets the matrix V of the decomposition.EigenDecompositionSymmetric.getV()
Gets the matrix V of the decomposition.SingularValueDecomposition.getV()
Returns the matrix V of the decomposition.EigenDecompositionNonSymmetric.getVInv()
Gets the inverse of the matrix V of the decomposition.EigenDecompositionSymmetric.getVT()
Gets the transpose of the matrix V of the decomposition.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.Array2DRowRealMatrix.kroneckerProduct
(RealMatrix b) Kronecker product of the current matrix and the parameter matrix.default RealMatrix
RealMatrix.map
(UnivariateFunction function) Acts as if implemented as:default RealMatrix
RealMatrix.mapToSelf
(UnivariateFunction function) Replace each entry by the result of applying the function to it.static RealMatrix
MatrixUtils.matrixExponential
(RealMatrix rm) Computes the matrix exponential of the given matrix.AbstractRealMatrix.multiply
(RealMatrix m) Returns the result of postmultiplyingthis
bym
.DiagonalMatrix.multiply
(RealMatrix m) Returns the result of postmultiplyingthis
bym
.OpenMapRealMatrix.multiply
(RealMatrix m) Returns the result of postmultiplyingthis
bym
.RealMatrix.multiply
(RealMatrix m) Returns the result of postmultiplyingthis
bym
.Array2DRowRealMatrix.multiplyTransposed
(Array2DRowRealMatrix m) Returns the result of postmultiplyingthis
bym^T
.Array2DRowRealMatrix.multiplyTransposed
(RealMatrix m) Returns the result of postmultiplyingthis
bym^T
.DiagonalMatrix.multiplyTransposed
(RealMatrix m) Returns the result of postmultiplyingthis
bym^T
.OpenMapRealMatrix.multiplyTransposed
(RealMatrix m) Returns the result of postmultiplyingthis
bym^T
.default RealMatrix
RealMatrix.multiplyTransposed
(RealMatrix m) Returns the result of postmultiplyingthis
bym^T
.ArrayRealVector.outerProduct
(RealVector v) Compute the outer product.RealVector.outerProduct
(RealVector v) Compute the outer product.Parse a string to produce aRealMatrix
object.RealMatrixFormat.parse
(String source, ParsePosition pos) Parse a string to produce aRealMatrix
object.AbstractRealMatrix.power
(int p) Returns the result of multiplyingthis
with itselfp
times.RealMatrix.power
(int p) Returns the result of multiplyingthis
with itselfp
times.AbstractRealMatrix.preMultiply
(RealMatrix m) Returns the result of premultiplyingthis
bym
.RealMatrix.preMultiply
(RealMatrix m) Returns the result of premultiplyingthis
bym
.AbstractRealMatrix.scalarAdd
(double d) Returns the result of addingd
to each entry ofthis
.RealMatrix.scalarAdd
(double d) Returns the result of addingd
to each entry ofthis
.AbstractRealMatrix.scalarMultiply
(double d) Returns the result of multiplying each entry ofthis
byd
.BlockRealMatrix.scalarMultiply
(double d) Returns the result of multiplying each entry ofthis
byd
.RealMatrix.scalarMultiply
(double d) Returns the result of multiplying each entry ofthis
byd
.DecompositionSolver.solve
(RealMatrix b) Solve the linear equation A × X = B for matrices A.Array2DRowRealMatrix.stack()
Transforms a matrix in a vector (Vectorization).AbstractRealMatrix.subtract
(RealMatrix m) Returnsthis
minusm
.RealMatrix.subtract
(RealMatrix m) Returnsthis
minusm
.AbstractRealMatrix.transpose()
Returns the transpose of this matrix.RealMatrix.transpose()
Returns the transpose of this matrix.Array2DRowRealMatrix.transposeMultiply
(Array2DRowRealMatrix m) Returns the result of postmultiplyingthis^T
bym
.Array2DRowRealMatrix.transposeMultiply
(RealMatrix m) Returns the result of postmultiplyingthis^T
bym
.DiagonalMatrix.transposeMultiply
(RealMatrix m) Returns the result of postmultiplyingthis^T
bym
.OpenMapRealMatrix.transposeMultiply
(RealMatrix m) Returns the result of postmultiplyingthis^T
bym
.default RealMatrix
RealMatrix.transposeMultiply
(RealMatrix m) Returns the result of postmultiplyingthis^T
bym
.Array2DRowRealMatrix.unstackSquare()
Transforms a one-column stacked matrix into a squared matrix (devectorization).Modifier and TypeMethodDescriptionAbstractRealMatrix.add
(RealMatrix m) Returns the sum ofthis
andm
.BlockRealMatrix.add
(RealMatrix m) Returns the sum ofthis
andm
.RealMatrix.add
(RealMatrix m) Returns the sum ofthis
andm
.default RealMatrix
RealMatrix.blendArithmeticallyWith
(RealMatrix other, double blendingValue) Blend arithmetically this instance with another one.static RealMatrix
MatrixUtils.blockInverse
(RealMatrix m, int splitIndex) Computes the inverse of the given matrix by splitting it into 4 sub-matrices.protected void
ComplexEigenDecomposition.checkDefinition
(RealMatrix matrix) Check definition of the decomposition in runtime.static void
MatrixUtils.checkSymmetric
(RealMatrix matrix, double eps) Checks whether a matrix is symmetric.CholeskyDecomposer.decompose
(RealMatrix a) Get a solver for finding the A × X = B solution in least square sense.LUDecomposer.decompose
(RealMatrix a) Get a solver for finding the A × X = B solution in least square sense.MatrixDecomposer.decompose
(RealMatrix a) Get a solver for finding the A × X = B solution in least square sense.QRDecomposer.decompose
(RealMatrix a) Get a solver for finding the A × X = B solution in least square sense.SingularValueDecomposer.decompose
(RealMatrix a) Get a solver for finding the A × X = B solution in least square sense.protected void
ComplexEigenDecomposition.findEigenValues
(RealMatrix matrix) Compute eigen values using the Schur transform.RealMatrixFormat.format
(RealMatrix m) This method callsRealMatrixFormat.format(RealMatrix,StringBuffer,FieldPosition)
.RealMatrixFormat.format
(RealMatrix matrix, StringBuffer toAppendTo, FieldPosition pos) Formats aRealMatrix
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.Array2DRowRealMatrix.kroneckerProduct
(RealMatrix b) Kronecker product of the current matrix and the parameter matrix.static RealMatrix
MatrixUtils.matrixExponential
(RealMatrix rm) Computes the matrix exponential of the given matrix.AbstractRealMatrix.multiply
(RealMatrix m) Returns the result of postmultiplyingthis
bym
.BlockRealMatrix.multiply
(RealMatrix m) Returns the result of postmultiplyingthis
bym
.DiagonalMatrix.multiply
(RealMatrix m) Returns the result of postmultiplyingthis
bym
.OpenMapRealMatrix.multiply
(RealMatrix m) Returns the result of postmultiplyingthis
bym
.RealMatrix.multiply
(RealMatrix m) Returns the result of postmultiplyingthis
bym
.Array2DRowRealMatrix.multiplyTransposed
(RealMatrix m) Returns the result of postmultiplyingthis
bym^T
.BlockRealMatrix.multiplyTransposed
(RealMatrix m) Returns the result of postmultiplyingthis
bym^T
.DiagonalMatrix.multiplyTransposed
(RealMatrix m) Returns the result of postmultiplyingthis
bym^T
.OpenMapRealMatrix.multiplyTransposed
(RealMatrix m) Returns the result of postmultiplyingthis
bym^T
.default RealMatrix
RealMatrix.multiplyTransposed
(RealMatrix m) Returns the result of postmultiplyingthis
bym^T
.AbstractRealMatrix.preMultiply
(RealMatrix m) Returns the result of premultiplyingthis
bym
.RealMatrix.preMultiply
(RealMatrix m) Returns the result of premultiplyingthis
bym
.void
AbstractRealMatrix.setColumnMatrix
(int column, RealMatrix matrix) Sets the specifiedcolumn
ofthis
matrix to the entries of the specified columnmatrix
.void
BlockRealMatrix.setColumnMatrix
(int column, RealMatrix matrix) Sets the specifiedcolumn
ofthis
matrix to the entries of the specified columnmatrix
.void
RealMatrix.setColumnMatrix
(int column, RealMatrix matrix) Sets the specifiedcolumn
ofthis
matrix to the entries of the specified columnmatrix
.void
AbstractRealMatrix.setRowMatrix
(int row, RealMatrix matrix) Sets the specifiedrow
ofthis
matrix to the entries of the specified rowmatrix
.void
BlockRealMatrix.setRowMatrix
(int row, RealMatrix matrix) Sets the specifiedrow
ofthis
matrix to the entries of the specified rowmatrix
.void
RealMatrix.setRowMatrix
(int row, RealMatrix matrix) Sets the specifiedrow
ofthis
matrix to the entries of the specified rowmatrix
.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 MatrixRealMatrix
.static void
MatrixUtils.solveUpperTriangularSystem
(RealMatrix rm, RealVector b) Solver a system composed of an Upper Triangular MatrixRealMatrix
.AbstractRealMatrix.subtract
(RealMatrix m) Returnsthis
minusm
.BlockRealMatrix.subtract
(RealMatrix m) Returnsthis
minusm
.OpenMapRealMatrix.subtract
(RealMatrix m) Returnsthis
minusm
.RealMatrix.subtract
(RealMatrix m) Returnsthis
minusm
.Array2DRowRealMatrix.transposeMultiply
(RealMatrix m) Returns the result of postmultiplyingthis^T
bym
.BlockRealMatrix.transposeMultiply
(RealMatrix m) Returns the result of postmultiplyingthis^T
bym
.DiagonalMatrix.transposeMultiply
(RealMatrix m) Returns the result of postmultiplyingthis^T
bym
.OpenMapRealMatrix.transposeMultiply
(RealMatrix m) Returns the result of postmultiplyingthis^T
bym
.default RealMatrix
RealMatrix.transposeMultiply
(RealMatrix m) Returns the result of postmultiplyingthis^T
bym
.ModifierConstructorDescriptionCholeskyDecomposition
(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.ComplexEigenDecomposition
(RealMatrix matrix) Constructor for decomposition.ComplexEigenDecomposition
(RealMatrix matrix, double eigenVectorsEquality, double epsilon, double epsilonAVVDCheck) Constructor for decomposition.Calculates the eigen decomposition of the given real matrix.EigenDecompositionNonSymmetric
(RealMatrix matrix, double epsilon) Calculates the eigen decomposition of the given real matrix.Calculates the eigen decomposition of the given symmetric real matrix.EigenDecompositionSymmetric
(RealMatrix matrix, double epsilon, boolean decreasing) Calculates the eigen decomposition of the given real matrix.HessenbergTransformer
(RealMatrix matrix) Build the transformation to Hessenberg form of a general matrix.LUDecomposition
(RealMatrix matrix) Calculates the LU-decomposition of the given matrix.LUDecomposition
(RealMatrix matrix, double singularityThreshold) Calculates the LU-decomposition of the given matrix.Constructor for the decomposition.OrderedComplexEigenDecomposition
(RealMatrix matrix, double eigenVectorsEquality, double epsilon, double epsilonAVVDCheck) Constructor for decomposition.OrderedComplexEigenDecomposition
(RealMatrix matrix, double eigenVectorsEquality, double epsilon, double epsilonAVVDCheck, Comparator<Complex> eigenValuesComparator) Constructor for decomposition.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.Constructor of the solver.RRQRDecomposition
(RealMatrix matrix) Calculates the QR-decomposition of the given matrix.RRQRDecomposition
(RealMatrix matrix, double threshold) Calculates the QR-decomposition of the given matrix.SchurTransformer
(RealMatrix matrix) Build the transformation to Schur form of a general real matrix.SchurTransformer
(RealMatrix matrix, double epsilon) Build the transformation to Schur form of a general real matrix.Calculates the Cholesky decomposition of the given matrix.SemiDefinitePositiveCholeskyDecomposition
(RealMatrix matrix, double positivityThreshold) Calculates the Cholesky decomposition of the given matrix.SingularValueDecomposition
(RealMatrix matrix) Calculates the compact Singular Value Decomposition of the given matrix. -
Uses of RealMatrix in org.hipparchus.ode.nonstiff
Modifier and TypeMethodDescriptionprotected double
AdamsBashforthIntegrator.errorEstimation
(double[] previousState, double predictedTime, double[] predictedState, double[] predictedScaled, RealMatrix predictedNordsieck) Estimate error.protected abstract double
AdamsIntegrator.errorEstimation
(double[] previousState, double predictedTime, double[] predictedState, double[] predictedScaled, RealMatrix predictedNordsieck) Estimate error.protected double
AdamsMoultonIntegrator.errorEstimation
(double[] previousState, double predictedTime, double[] predictedState, double[] predictedScaled, RealMatrix predictedNordsieck) Estimate error. -
Uses of RealMatrix in org.hipparchus.optim.nonlinear.scalar
ModifierConstructorDescriptionLeastSquaresConverter
(MultivariateVectorFunction function, double[] observations, RealMatrix scale) Builds a simple converter for correlated residuals with the specified weights. -
Uses of RealMatrix in org.hipparchus.optim.nonlinear.scalar.noderiv
Modifier and TypeMethodDescriptionCMAESOptimizer.getStatisticsDHistory()
Get history of D matrix.CMAESOptimizer.getStatisticsMeanHistory()
Get history of mean matrix. -
Uses of RealMatrix in org.hipparchus.optim.nonlinear.vector.constrained
Modifier and TypeMethodDescriptionLinearEqualityConstraint.getA()
Get the matrix of linear weights.QuadraticFunction.getP()
Get square matrix of weights for quadratic terms.ADMMQPModifiedRuizEquilibrium.getScaledA()
Get scaled constraints coefficients matrix.ADMMQPModifiedRuizEquilibrium.getScaledH()
Get scaled square matrix of weights for quadratic terms.default RealMatrix
VectorDifferentiableFunction.gradient
(double[] x) Returns the gradient of this function at (x)QuadraticFunction.hessian
(RealVector x) The Hessian of this function at (x)TwiceDifferentiableFunction.hessian
(double[] x) The Hessian of this function at (x)abstract RealMatrix
TwiceDifferentiableFunction.hessian
(RealVector x) The Hessian of this function at (x)LinearBoundedConstraint.jacobian
(RealVector x) Returns the gradient of this function at (x)LinearEqualityConstraint.jacobian
(RealVector x) LinearInequalityConstraint.jacobian
(RealVector x) VectorDifferentiableFunction.jacobian
(RealVector x) Returns the gradient of this function at (x)Modifier and TypeMethodDescriptionvoid
ADMMQPKKT.initialize
(RealMatrix newH, RealMatrix newA, RealVector newQ, int me, RealVector newLb, RealVector newUb, double rho, double newSigma, double newAlpha) Initialize problemprotected RealVector
AbstractSQPOptimizer.lagrangianGradX
(RealVector currentGrad, RealMatrix jacobConstraint, RealVector x, RealVector y) Compute Lagrangian gradient for variable XModifierConstructorDescriptionSimple constructorLinearBoundedConstraint
(RealMatrix a, RealVector lower, RealVector upper) Construct a set of linear inequality constraints from Ax < BConstruct a set of linear equality constraints ax = b.Construct a set of linear inequality constraints from \( A x \gt B\).QuadraticFunction
(RealMatrix p, RealVector q, double d) Construct quadratic function \(\frac{1}{2}x^T P X + Q^T x + d\). -
Uses of RealMatrix in org.hipparchus.optim.nonlinear.vector.leastsquares
Modifier 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.Modifier and TypeMethodDescriptionMultivariateJacobianFunction.value
(RealVector point) Compute the function value and its Jacobian.Modifier and TypeMethodDescriptionstatic LeastSquaresProblem
LeastSquaresFactory.create
(MultivariateVectorFunction model, MultivariateMatrixFunction jacobian, double[] observed, double[] start, RealMatrix weight, ConvergenceChecker<LeastSquaresProblem.Evaluation> checker, int maxEvaluations, int maxIterations) Create aLeastSquaresProblem
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 aLeastSquaresProblem
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 aLeastSquaresProblem
from the given elements.LeastSquaresBuilder.weight
(RealMatrix newWeight) Configure the weight matrix.static LeastSquaresProblem
LeastSquaresFactory.weightMatrix
(LeastSquaresProblem problem, RealMatrix weights) Apply a dense weight matrix to theLeastSquaresProblem
.SequentialGaussNewtonOptimizer.withAPrioriData
(RealVector aPrioriState, RealMatrix aPrioriCovariance) Configure from a priori state and covariance.SequentialGaussNewtonOptimizer.withAPrioriData
(RealVector aPrioriState, RealMatrix aPrioriCovariance, double relativeSymmetryThreshold, double absolutePositivityThreshold) Configure from a priori state and covariance. -
Uses of RealMatrix in org.hipparchus.random
Modifier and TypeMethodDescriptionCorrelatedRandomVectorGenerator.getRootMatrix()
Get the root of the covariance matrix.ModifierConstructorDescriptionCorrelatedRandomVectorGenerator
(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.hipparchus.stat.correlation
Modifier 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 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.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 matrixModifier 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 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.PearsonsCorrelation.covarianceToCorrelation
(RealMatrix covarianceMatrix) Derives a correlation matrix from a covariance matrix.ModifierConstructorDescriptionCovariance
(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.hipparchus.stat.descriptive
Modifier and TypeMethodDescriptionMultivariateSummaryStatistics.getCovariance()
Returns the covariance of the available values.StatisticalMultivariateSummary.getCovariance()
Returns the covariance of the available values. -
Uses of RealMatrix in org.hipparchus.stat.descriptive.vector
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Uses of RealMatrix in org.hipparchus.stat.regression
Modifier and TypeMethodDescriptionprotected 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.OLSMultipleLinearRegression.calculateHat()
Compute the "hat" matrix.protected RealMatrix
GLSMultipleLinearRegression.getOmegaInverse()
Get the inverse of the covariance.protected RealMatrix
AbstractMultipleLinearRegression.getX()
Get the X sample data. -
Uses of RealMatrix in org.hipparchus.util
Modifier and TypeMethodDescriptiondefault RealMatrix
UnscentedTransformProvider.getUnscentedCovariance
(RealVector[] sigmaPoints, RealVector meanState) Computes the unscented covariance matrix from a weighted mean state and a set of sigma points.Modifier and TypeMethodDescriptiondefault Pair<RealVector,
RealMatrix> UnscentedTransformProvider.inverseUnscentedTransform
(RealVector[] sigmaPoints) Perform the inverse unscented transform from an array of sigma points.Modifier and TypeMethodDescriptionAbstractUnscentedTransform.unscentedTransform
(RealVector state, RealMatrix covariance) Perform the unscented transform from a state and its covariance.UnscentedTransformProvider.unscentedTransform
(RealVector state, RealMatrix covariance) Perform the unscented transform from a state and its covariance.