Package | Description |
---|---|
org.hipparchus.clustering |
Clustering algorithms.
|
org.hipparchus.distribution.multivariate |
Implementations of multivariate distributions.
|
org.hipparchus.filtering.kalman |
Kalman filter.
|
org.hipparchus.filtering.kalman.extended |
Kalman filter implementation for non-linear processes.
|
org.hipparchus.filtering.kalman.linear |
Kalman filter implementation for linear processes.
|
org.hipparchus.linear |
Linear algebra support.
|
org.hipparchus.optim.nonlinear.scalar |
Algorithms for optimizing a scalar function.
|
org.hipparchus.optim.nonlinear.scalar.noderiv |
This package provides optimization algorithms that do not require derivatives.
|
org.hipparchus.optim.nonlinear.vector.leastsquares |
This package provides algorithms that minimize the residuals
between observations and model values.
|
org.hipparchus.random |
Random number and random data generators.
|
org.hipparchus.stat.correlation |
Correlations/Covariance computations.
|
org.hipparchus.stat.descriptive |
Generic univariate and multivariate summary statistic objects.
|
org.hipparchus.stat.descriptive.vector |
Multivariate statistics.
|
org.hipparchus.stat.regression |
Statistical routines involving multivariate data.
|
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. |
Modifier and Type | Method | Description |
---|---|---|
RealMatrix |
MultivariateNormalDistribution.getCovariances() |
Gets the covariance matrix.
|
Modifier and Type | Method | Description |
---|---|---|
protected RealMatrix |
AbstractKalmanFilter.computeInnovationCovarianceMatrix(RealMatrix r,
RealMatrix h) |
Compute innovation covariance matrix.
|
RealMatrix |
Measurement.getCovariance() |
Get the measurement covariance.
|
RealMatrix |
ProcessEstimate.getCovariance() |
Get the state covariance.
|
Modifier and Type | Method | Description |
---|---|---|
protected RealMatrix |
AbstractKalmanFilter.computeInnovationCovarianceMatrix(RealMatrix r,
RealMatrix h) |
Compute innovation covariance matrix.
|
protected void |
AbstractKalmanFilter.correct(T measurement,
RealVector innovation,
RealMatrix h,
RealMatrix s) |
Perform correction step.
|
protected void |
AbstractKalmanFilter.predict(double time,
RealVector predictedState,
RealMatrix stm,
RealMatrix noise) |
Perform prediction step.
|
Constructor | Description |
---|---|
ProcessEstimate(double time,
RealVector state,
RealMatrix covariance) |
Simple constructor.
|
Modifier and Type | Method | Description |
---|---|---|
RealMatrix |
NonLinearEvolution.getMeasurementJacobian() |
Get measurement Jacobian.
|
RealMatrix |
NonLinearEvolution.getProcessNoiseMatrix() |
Get process noise.
|
RealMatrix |
NonLinearEvolution.getStateTransitionMatrix() |
Get state transition matrix between previous and current state.
|
Modifier and Type | Method | Description |
---|---|---|
RealVector |
NonLinearProcess.getInnovation(T measurement,
NonLinearEvolution evolution,
RealMatrix innovationCovarianceMatrix) |
Get the innovation brought by a measurement.
|
Constructor | Description |
---|---|
NonLinearEvolution(double currentTime,
RealVector currentState,
RealMatrix stateTransitionMatrix,
RealMatrix processNoiseMatrix,
RealMatrix measurementJacobian) |
Simple constructor.
|
Modifier and Type | Method | Description |
---|---|---|
RealMatrix |
LinearEvolution.getControlMatrix() |
Get the control matrix Bk-1.
|
RealMatrix |
LinearEvolution.getMeasurementJacobian() |
Get measurement Jacobian.
|
RealMatrix |
LinearEvolution.getProcessNoiseMatrix() |
Get the process noise matrix Qk-1.
|
RealMatrix |
LinearEvolution.getStateTransitionMatrix() |
Get the state transition matrix Ak-1.
|
Constructor | Description |
---|---|
LinearEvolution(RealMatrix stateTransitionMatrix,
RealMatrix controlMatrix,
RealVector command,
RealMatrix processNoiseMatrix,
RealMatrix measurementJacobian) |
Simple constructor.
|
Modifier and Type | Interface | Description |
---|---|---|
interface |
SparseRealMatrix |
Marker interface for
RealMatrix implementations that require sparse backing storage |
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.
|
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 |
RiccatiEquationSolver.getK() |
Get the linear controller k.
|
RealMatrix |
RiccatiEquationSolverImpl.getK() |
{inheritDoc}
|
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 |
RiccatiEquationSolver.getP() |
Get the solution.
|
RealMatrix |
RiccatiEquationSolverImpl.getP() |
{inheritDoc}
|
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 |
Array2DRowRealMatrix.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 |
OrderedEigenDecomposition.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 |
Array2DRowRealMatrix.kroneckerProduct(RealMatrix b) |
Kronecker product of the current matrix and the parameter 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 |
Array2DRowRealMatrix.multiplyTransposed(Array2DRowRealMatrix m) |
Returns the result of postmultiplying
this by m^T . |
RealMatrix |
Array2DRowRealMatrix.multiplyTransposed(RealMatrix m) |
Returns the result of postmultiplying
this by m^T . |
RealMatrix |
DiagonalMatrix.multiplyTransposed(RealMatrix m) |
Returns the result of postmultiplying
this by m^T . |
RealMatrix |
OpenMapRealMatrix.multiplyTransposed(RealMatrix m) |
Returns the result of postmultiplying
this by m^T . |
default RealMatrix |
RealMatrix.multiplyTransposed(RealMatrix m) |
Returns the result of postmultiplying
this by m^T . |
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 |
Array2DRowRealMatrix.stack() |
Transforms a matrix in a vector (Vectorization).
|
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.
|
RealMatrix |
Array2DRowRealMatrix.transposeMultiply(Array2DRowRealMatrix m) |
Returns the result of postmultiplying
this^T by m . |
RealMatrix |
Array2DRowRealMatrix.transposeMultiply(RealMatrix m) |
Returns the result of postmultiplying
this^T by m . |
RealMatrix |
DiagonalMatrix.transposeMultiply(RealMatrix m) |
Returns the result of postmultiplying
this^T by m . |
RealMatrix |
OpenMapRealMatrix.transposeMultiply(RealMatrix m) |
Returns the result of postmultiplying
this^T by m . |
default RealMatrix |
RealMatrix.transposeMultiply(RealMatrix m) |
Returns the result of postmultiplying
this^T by m . |
RealMatrix |
Array2DRowRealMatrix.unstackSquare() |
Transforms a one-column stacked matrix into a squared matrix (devectorization).
|
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.
|
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.
|
DecompositionSolver |
CholeskyDecomposer.decompose(RealMatrix a) |
Get a solver for finding the A × X = B solution in least square sense.
|
DecompositionSolver |
LUDecomposer.decompose(RealMatrix a) |
Get a solver for finding the A × X = B solution in least square sense.
|
DecompositionSolver |
MatrixDecomposer.decompose(RealMatrix a) |
Get a solver for finding the A × X = B solution in least square sense.
|
DecompositionSolver |
QRDecomposer.decompose(RealMatrix a) |
Get a solver for finding the A × X = B solution in least square sense.
|
DecompositionSolver |
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.
|
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 |
Array2DRowRealMatrix.kroneckerProduct(RealMatrix b) |
Kronecker product of the current matrix and the parameter matrix.
|
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 |
Array2DRowRealMatrix.multiplyTransposed(RealMatrix m) |
Returns the result of postmultiplying
this by m^T . |
BlockRealMatrix |
BlockRealMatrix.multiplyTransposed(RealMatrix m) |
Returns the result of postmultiplying
this by m^T . |
RealMatrix |
DiagonalMatrix.multiplyTransposed(RealMatrix m) |
Returns the result of postmultiplying
this by m^T . |
RealMatrix |
OpenMapRealMatrix.multiplyTransposed(RealMatrix m) |
Returns the result of postmultiplying
this by m^T . |
default RealMatrix |
RealMatrix.multiplyTransposed(RealMatrix m) |
Returns the result of postmultiplying
this by m^T . |
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 . |
RealMatrix |
Array2DRowRealMatrix.transposeMultiply(RealMatrix m) |
Returns the result of postmultiplying
this^T by m . |
BlockRealMatrix |
BlockRealMatrix.transposeMultiply(RealMatrix m) |
Returns the result of postmultiplying
this^T by m . |
RealMatrix |
DiagonalMatrix.transposeMultiply(RealMatrix m) |
Returns the result of postmultiplying
this^T by m . |
RealMatrix |
OpenMapRealMatrix.transposeMultiply(RealMatrix m) |
Returns the result of postmultiplying
this^T by m . |
default RealMatrix |
RealMatrix.transposeMultiply(RealMatrix m) |
Returns the result of postmultiplying
this^T by m . |
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.
|
ComplexEigenDecomposition(RealMatrix matrix) |
Constructor for decomposition.
|
EigenDecomposition(RealMatrix matrix) |
Calculates the eigen decomposition of the given real 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.
|
OrderedComplexEigenDecomposition(RealMatrix matrix) |
Constructor for the decomposition.
|
OrderedEigenDecomposition(RealMatrix matrix) |
Constructor using the EigenDecomposition as starting point for ordering.
|
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.
|
RiccatiEquationSolverImpl(RealMatrix A,
RealMatrix B,
RealMatrix Q,
RealMatrix R) |
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.
|
SingularValueDecomposition(RealMatrix matrix) |
Calculates the compact Singular Value Decomposition of the given matrix.
|
Constructor | Description |
---|---|
LeastSquaresConverter(MultivariateVectorFunction function,
double[] observations,
RealMatrix scale) |
Builds a simple converter for correlated residuals with the
specified weights.
|
Modifier and Type | Method | Description |
---|---|---|
List<RealMatrix> |
CMAESOptimizer.getStatisticsDHistory() |
|
List<RealMatrix> |
CMAESOptimizer.getStatisticsMeanHistory() |
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.
|
Modifier and Type | Method | Description |
---|---|---|
Pair<RealVector,RealMatrix> |
MultivariateJacobianFunction.value(RealVector point) |
Compute the function value and its Jacobian.
|
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) |
Deprecated.
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 . |
Modifier and Type | Method | Description |
---|---|---|
RealMatrix |
CorrelatedRandomVectorGenerator.getRootMatrix() |
Get the root of the covariance matrix.
|
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.
|
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
|
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.
|
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.
|
Modifier and Type | Method | Description |
---|---|---|
RealMatrix |
MultivariateSummaryStatistics.getCovariance() |
Returns the covariance of the available values.
|
RealMatrix |
StatisticalMultivariateSummary.getCovariance() |
Returns the covariance of the available values.
|
Modifier and Type | Method | Description |
---|---|---|
RealMatrix |
VectorialCovariance.getResult() |
Get the covariance matrix.
|
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() |
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