| Package | Description | 
|---|---|
| org.hipparchus.clustering | 
 Clustering algorithms. 
 | 
| org.hipparchus.distribution.multivariate | 
 Implementations of multivariate distributions. 
 | 
| 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 and 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 and Description | 
|---|---|
RealMatrix | 
MultivariateNormalDistribution.getCovariances()
Gets the covariance matrix. 
 | 
| Modifier and Type | Interface and Description | 
|---|---|
interface  | 
SparseRealMatrix
Marker interface for  
RealMatrix implementations that require sparse backing storage | 
| Modifier and Type | Class and Description | 
|---|---|
class  | 
AbstractRealMatrix
Basic implementation of RealMatrix methods regardless of the underlying storage. 
 | 
class  | 
Array2DRowRealMatrix
Implementation of  
RealMatrix using a double[][] array to
 store entries. | 
class  | 
BlockRealMatrix
Cache-friendly implementation of RealMatrix using a flat arrays to store
 square blocks of the matrix. 
 | 
class  | 
DiagonalMatrix
Implementation of a diagonal matrix. 
 | 
class  | 
OpenMapRealMatrix
Sparse matrix implementation based on an open addressed map. 
 | 
| Modifier and Type | Method and Description | 
|---|---|
RealMatrix | 
RealMatrix.add(RealMatrix m)
Returns the sum of  
this and m. | 
RealMatrix | 
AbstractRealMatrix.add(RealMatrix m)
Returns the sum of  
this and m. | 
static RealMatrix | 
MatrixUtils.blockInverse(RealMatrix m,
            int splitIndex)
Computes the inverse of the given matrix by splitting it into
 4 sub-matrices. 
 | 
RealMatrix | 
RealMatrix.copy()
Returns a (deep) copy of this. 
 | 
RealMatrix | 
Array2DRowRealMatrix.copy()
Returns a (deep) copy of this. 
 | 
abstract RealMatrix | 
AbstractRealMatrix.copy()
Returns a (deep) copy of this. 
 | 
RealMatrix | 
DiagonalMatrix.copy()
Returns a (deep) copy of this. 
 | 
static RealMatrix | 
MatrixUtils.createColumnRealMatrix(double[] columnData)
Creates a column  
RealMatrix using the data from the input
 array. | 
RealMatrix | 
RealMatrix.createMatrix(int rowDimension,
            int columnDimension)
Create a new RealMatrix of the same type as the instance with the
 supplied
 row and column dimensions. 
 | 
RealMatrix | 
Array2DRowRealMatrix.createMatrix(int rowDimension,
            int columnDimension)
Create a new RealMatrix of the same type as the instance with the
 supplied
 row and column dimensions. 
 | 
abstract RealMatrix | 
AbstractRealMatrix.createMatrix(int rowDimension,
            int columnDimension)
Create a new RealMatrix of the same type as the instance with the
 supplied
 row and column dimensions. 
 | 
RealMatrix | 
DiagonalMatrix.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 | 
RealMatrix.getColumnMatrix(int column)
Get the entries at the given column index as a column matrix. 
 | 
RealMatrix | 
AbstractRealMatrix.getColumnMatrix(int column)
Get the entries at the given column index as a column matrix. 
 | 
RealMatrix | 
SingularValueDecomposition.getCovariance(double minSingularValue)
Returns the n × n covariance matrix. 
 | 
RealMatrix | 
EigenDecomposition.getD()
Gets the block diagonal matrix D of the decomposition. 
 | 
RealMatrix | 
QRDecomposition.getH()
Returns the Householder reflector vectors. 
 | 
RealMatrix | 
DecompositionSolver.getInverse()
Get the pseudo-inverse
 of the decomposed matrix. 
 | 
RealMatrix | 
CholeskyDecomposition.getL()
Returns the matrix L of the decomposition. 
 | 
RealMatrix | 
LUDecomposition.getL()
Returns the matrix L of the decomposition. 
 | 
RealMatrix | 
CholeskyDecomposition.getLT()
Returns the transpose of the matrix L of the decomposition. 
 | 
RealMatrix | 
RRQRDecomposition.getP()
Returns the pivot matrix, P, used in the QR Decomposition of matrix A such that AP = QR. 
 | 
RealMatrix | 
LUDecomposition.getP()
Returns the P rows permutation matrix. 
 | 
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 | 
RealMatrix.getRowMatrix(int row)
Get the entries at the given row index as a row matrix. 
 | 
RealMatrix | 
AbstractRealMatrix.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 | 
RealMatrix.getSubMatrix(int[] selectedRows,
            int[] selectedColumns)
Gets a submatrix. 
 | 
RealMatrix | 
AbstractRealMatrix.getSubMatrix(int[] selectedRows,
            int[] selectedColumns)
Gets a submatrix. 
 | 
RealMatrix | 
RealMatrix.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 | 
AbstractRealMatrix.getSubMatrix(int startRow,
            int endRow,
            int startColumn,
            int endColumn)
Gets a submatrix. 
 | 
RealMatrix | 
SingularValueDecomposition.getU()
Returns the matrix U of the decomposition. 
 | 
RealMatrix | 
LUDecomposition.getU()
Returns the matrix U of the decomposition. 
 | 
RealMatrix | 
SingularValueDecomposition.getUT()
Returns the transpose of the matrix U of the decomposition. 
 | 
RealMatrix | 
EigenDecomposition.getV()
Gets the matrix V of the decomposition. 
 | 
RealMatrix | 
SingularValueDecomposition.getV()
Returns the matrix V of the decomposition. 
 | 
RealMatrix | 
EigenDecomposition.getVT()
Gets the transpose of the matrix V of the decomposition. 
 | 
RealMatrix | 
SingularValueDecomposition.getVT()
Returns the transpose of the matrix V of the decomposition. 
 | 
static RealMatrix | 
MatrixUtils.inverse(RealMatrix matrix)
Computes the inverse of the given matrix. 
 | 
static RealMatrix | 
MatrixUtils.inverse(RealMatrix matrix,
       double threshold)
Computes the inverse of the given matrix. 
 | 
RealMatrix | 
RealMatrix.multiply(RealMatrix m)
Returns the result of postmultiplying  
this by m. | 
RealMatrix | 
AbstractRealMatrix.multiply(RealMatrix m)
Returns the result of postmultiplying  
this by m. | 
RealMatrix | 
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 | 
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 | 
RealMatrix.power(int p)
Returns the result of multiplying  
this with itself p
 times. | 
RealMatrix | 
AbstractRealMatrix.power(int p)
Returns the result of multiplying  
this with itself p
 times. | 
RealMatrix | 
RealMatrix.preMultiply(RealMatrix m)
Returns the result of premultiplying  
this by m. | 
RealMatrix | 
AbstractRealMatrix.preMultiply(RealMatrix m)
Returns the result of premultiplying  
this by m. | 
RealMatrix | 
RealMatrix.scalarAdd(double d)
Returns the result of adding  
d to each entry of this. | 
RealMatrix | 
AbstractRealMatrix.scalarAdd(double d)
Returns the result of adding  
d to each entry of this. | 
RealMatrix | 
RealMatrix.scalarMultiply(double d)
Returns the result of multiplying each entry of  
this by
 d. | 
RealMatrix | 
AbstractRealMatrix.scalarMultiply(double d)
Returns the result of multiplying each entry of  
this by
 d. | 
RealMatrix | 
BlockRealMatrix.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 | 
RealMatrix.subtract(RealMatrix m)
Returns  
this minus m. | 
RealMatrix | 
AbstractRealMatrix.subtract(RealMatrix m)
Returns  
this minus m. | 
RealMatrix | 
RealMatrix.transpose()
Returns the transpose of this matrix. 
 | 
RealMatrix | 
AbstractRealMatrix.transpose()
Returns the transpose of this matrix. 
 | 
| Modifier and Type | Method and Description | 
|---|---|
RealMatrix | 
RealMatrix.add(RealMatrix m)
Returns the sum of  
this and m. | 
RealMatrix | 
AbstractRealMatrix.add(RealMatrix m)
Returns the sum of  
this and m. | 
BlockRealMatrix | 
BlockRealMatrix.add(RealMatrix m)
Returns the sum of  
this and m. | 
static RealMatrix | 
MatrixUtils.blockInverse(RealMatrix m,
            int splitIndex)
Computes the inverse of the given matrix by splitting it into
 4 sub-matrices. 
 | 
static void | 
MatrixUtils.checkSymmetric(RealMatrix matrix,
              double eps)
Checks whether a matrix is symmetric. 
 | 
String | 
RealMatrixFormat.format(RealMatrix m)
This method calls  
RealMatrixFormat.format(RealMatrix,StringBuffer,FieldPosition). | 
StringBuffer | 
RealMatrixFormat.format(RealMatrix matrix,
      StringBuffer toAppendTo,
      FieldPosition pos)
Formats a  
RealMatrix object to produce a string. | 
static RealMatrix | 
MatrixUtils.inverse(RealMatrix matrix)
Computes the inverse of the given matrix. 
 | 
static RealMatrix | 
MatrixUtils.inverse(RealMatrix matrix,
       double threshold)
Computes the inverse of the given matrix. 
 | 
static boolean | 
MatrixUtils.isSymmetric(RealMatrix matrix,
           double eps)
Checks whether a matrix is symmetric. 
 | 
RealMatrix | 
RealMatrix.multiply(RealMatrix m)
Returns the result of postmultiplying  
this by m. | 
RealMatrix | 
AbstractRealMatrix.multiply(RealMatrix m)
Returns the result of postmultiplying  
this by m. | 
RealMatrix | 
DiagonalMatrix.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 | 
OpenMapRealMatrix.multiply(RealMatrix m)
Returns the result of postmultiplying  
this by m. | 
RealMatrix | 
RealMatrix.preMultiply(RealMatrix m)
Returns the result of premultiplying  
this by m. | 
RealMatrix | 
AbstractRealMatrix.preMultiply(RealMatrix m)
Returns the result of premultiplying  
this by m. | 
static void | 
MatrixUtils.serializeRealMatrix(RealMatrix matrix,
                   ObjectOutputStream oos)
Serialize a  
RealMatrix. | 
void | 
RealMatrix.setColumnMatrix(int column,
               RealMatrix matrix)
Sets the specified  
column of this matrix to the entries
 of the specified column matrix. | 
void | 
AbstractRealMatrix.setColumnMatrix(int column,
               RealMatrix matrix)
Sets the specified  
column of this matrix to the entries
 of the specified column matrix. | 
void | 
BlockRealMatrix.setColumnMatrix(int column,
               RealMatrix matrix)
Sets the specified  
column of this matrix to the entries
 of the specified column matrix. | 
void | 
RealMatrix.setRowMatrix(int row,
            RealMatrix matrix)
Sets the specified  
row of this matrix to the entries of
 the specified row matrix. | 
void | 
AbstractRealMatrix.setRowMatrix(int row,
            RealMatrix matrix)
Sets the specified  
row of this matrix to the entries of
 the specified row matrix. | 
void | 
BlockRealMatrix.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 | 
RealMatrix.subtract(RealMatrix m)
Returns  
this minus m. | 
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. | 
| Constructor and Description | 
|---|
CholeskyDecomposition(RealMatrix matrix)
Calculates the Cholesky decomposition of the given matrix. 
 | 
CholeskyDecomposition(RealMatrix matrix,
                     double relativeSymmetryThreshold,
                     double absolutePositivityThreshold)
Calculates the Cholesky decomposition of the given matrix. 
 | 
EigenDecomposition(RealMatrix matrix)
Calculates the eigen decomposition of the given real matrix. 
 | 
LUDecomposition(RealMatrix matrix)
Calculates the LU-decomposition of the given matrix. 
 | 
LUDecomposition(RealMatrix matrix,
               double singularityThreshold)
Calculates the LU-decomposition of the given matrix. 
 | 
QRDecomposition(RealMatrix matrix)
Calculates the QR-decomposition of the given matrix. 
 | 
QRDecomposition(RealMatrix matrix,
               double threshold)
Calculates the QR-decomposition of the given matrix. 
 | 
RectangularCholeskyDecomposition(RealMatrix matrix)
Decompose a symmetric positive semidefinite matrix. 
 | 
RectangularCholeskyDecomposition(RealMatrix matrix,
                                double small)
Decompose a symmetric positive semidefinite matrix. 
 | 
RRQRDecomposition(RealMatrix matrix)
Calculates the QR-decomposition of the given matrix. 
 | 
RRQRDecomposition(RealMatrix matrix,
                 double threshold)
Calculates the QR-decomposition of the given matrix. 
 | 
SingularValueDecomposition(RealMatrix matrix)
Calculates the compact Singular Value Decomposition of the given matrix. 
 | 
| Constructor and Description | 
|---|
LeastSquaresConverter(MultivariateVectorFunction function,
                     double[] observations,
                     RealMatrix scale)
Builds a simple converter for correlated residuals with the
 specified weights. 
 | 
| Modifier and Type | Method and Description | 
|---|---|
List<RealMatrix> | 
CMAESOptimizer.getStatisticsDHistory()  | 
List<RealMatrix> | 
CMAESOptimizer.getStatisticsMeanHistory()  | 
| Modifier and Type | Method and Description | 
|---|---|
RealMatrix | 
ValueAndJacobianFunction.computeJacobian(double[] params)
Compute the Jacobian. 
 | 
RealMatrix | 
LeastSquaresProblem.Evaluation.getCovariances(double threshold)
Get the covariance matrix of the optimized parameters. 
 | 
RealMatrix | 
AbstractEvaluation.getCovariances(double threshold)
Get the covariance matrix of the optimized parameters. 
 | 
RealMatrix | 
LeastSquaresProblem.Evaluation.getJacobian()
Get the weighted Jacobian matrix. 
 | 
| Modifier and Type | Method and Description | 
|---|---|
Pair<RealVector,RealMatrix> | 
MultivariateJacobianFunction.value(RealVector point)
Compute the function value and its Jacobian. 
 | 
| Modifier and Type | Method and Description | 
|---|---|
static LeastSquaresProblem | 
LeastSquaresFactory.create(MultivariateJacobianFunction model,
      RealVector observed,
      RealVector start,
      RealMatrix weight,
      ConvergenceChecker<LeastSquaresProblem.Evaluation> checker,
      int maxEvaluations,
      int maxIterations)
Create a  
LeastSquaresProblem
 from the given elements. | 
static LeastSquaresProblem | 
LeastSquaresFactory.create(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. | 
static LeastSquaresProblem | 
LeastSquaresFactory.create(MultivariateVectorFunction model,
      MultivariateMatrixFunction jacobian,
      double[] observed,
      double[] start,
      RealMatrix weight,
      ConvergenceChecker<LeastSquaresProblem.Evaluation> checker,
      int maxEvaluations,
      int maxIterations)
Create a  
LeastSquaresProblem
 from the given elements. | 
protected abstract RealVector | 
GaussNewtonOptimizer.Decomposition.solve(RealMatrix jacobian,
     RealVector residuals)
Solve the linear least squares problem Jx=r. 
 | 
LeastSquaresBuilder | 
LeastSquaresBuilder.weight(RealMatrix newWeight)
Configure the weight matrix. 
 | 
static LeastSquaresProblem | 
LeastSquaresFactory.weightMatrix(LeastSquaresProblem problem,
            RealMatrix weights)
Apply a dense weight matrix to the  
LeastSquaresProblem. | 
| Modifier and Type | Method and Description | 
|---|---|
RealMatrix | 
CorrelatedRandomVectorGenerator.getRootMatrix()
Get the root of the covariance matrix. 
 | 
| Constructor and Description | 
|---|
CorrelatedRandomVectorGenerator(double[] mean,
                               RealMatrix covariance,
                               double small,
                               NormalizedRandomGenerator generator)
Builds a correlated random vector generator from its mean
 vector and covariance matrix. 
 | 
CorrelatedRandomVectorGenerator(RealMatrix covariance,
                               double small,
                               NormalizedRandomGenerator generator)
Builds a null mean random correlated vector generator from its
 covariance matrix. 
 | 
| Modifier and Type | Method and Description | 
|---|---|
RealMatrix | 
SpearmansCorrelation.computeCorrelationMatrix(double[][] matrix)
Computes the Spearman's rank correlation matrix for the columns of the
 input rectangular array. 
 | 
RealMatrix | 
KendallsCorrelation.computeCorrelationMatrix(double[][] matrix)
Computes the Kendall's Tau rank correlation matrix for the columns of
 the input rectangular array. 
 | 
RealMatrix | 
PearsonsCorrelation.computeCorrelationMatrix(double[][] data)
Computes the correlation matrix for the columns of the
 input rectangular array. 
 | 
RealMatrix | 
SpearmansCorrelation.computeCorrelationMatrix(RealMatrix matrix)
Computes the Spearman's rank correlation matrix for the columns of the
 input matrix. 
 | 
RealMatrix | 
KendallsCorrelation.computeCorrelationMatrix(RealMatrix matrix)
Computes the Kendall's Tau rank correlation matrix for the columns of
 the input matrix. 
 | 
RealMatrix | 
PearsonsCorrelation.computeCorrelationMatrix(RealMatrix matrix)
Computes the correlation matrix for the columns of the
 input matrix, using  
PearsonsCorrelation.correlation(double[], double[]). | 
protected RealMatrix | 
Covariance.computeCovarianceMatrix(double[][] data)
Create a covariance matrix from a rectangular array whose columns represent
 covariates. 
 | 
protected RealMatrix | 
Covariance.computeCovarianceMatrix(double[][] data,
                       boolean biasCorrected)
Compute a covariance matrix from a rectangular array whose columns represent covariates. 
 | 
protected RealMatrix | 
Covariance.computeCovarianceMatrix(RealMatrix matrix)
Create a covariance matrix from a matrix whose columns represent
 covariates. 
 | 
protected RealMatrix | 
Covariance.computeCovarianceMatrix(RealMatrix matrix,
                       boolean biasCorrected)
Compute a covariance matrix from a matrix whose columns represent covariates. 
 | 
RealMatrix | 
PearsonsCorrelation.covarianceToCorrelation(RealMatrix covarianceMatrix)
Derives a correlation matrix from a covariance matrix. 
 | 
RealMatrix | 
SpearmansCorrelation.getCorrelationMatrix()
Calculate the Spearman Rank Correlation Matrix. 
 | 
RealMatrix | 
KendallsCorrelation.getCorrelationMatrix()
Returns the correlation matrix. 
 | 
RealMatrix | 
PearsonsCorrelation.getCorrelationMatrix()
Returns the correlation matrix. 
 | 
RealMatrix | 
PearsonsCorrelation.getCorrelationPValues()
Returns a matrix of p-values associated with the (two-sided) null
 hypothesis that the corresponding correlation coefficient is zero. 
 | 
RealMatrix | 
PearsonsCorrelation.getCorrelationStandardErrors()
Returns a matrix of standard errors associated with the estimates
 in the correlation matrix. 
getCorrelationStandardErrors().getEntry(i,j) is the standard
 error associated with getCorrelationMatrix.getEntry(i,j) | 
RealMatrix | 
StorelessCovariance.getCovarianceMatrix()
Returns the covariance matrix 
 | 
RealMatrix | 
Covariance.getCovarianceMatrix()
Returns the covariance matrix 
 | 
| Modifier and Type | Method and Description | 
|---|---|
RealMatrix | 
SpearmansCorrelation.computeCorrelationMatrix(RealMatrix matrix)
Computes the Spearman's rank correlation matrix for the columns of the
 input matrix. 
 | 
RealMatrix | 
KendallsCorrelation.computeCorrelationMatrix(RealMatrix matrix)
Computes the Kendall's Tau rank correlation matrix for the columns of
 the input matrix. 
 | 
RealMatrix | 
PearsonsCorrelation.computeCorrelationMatrix(RealMatrix matrix)
Computes the correlation matrix for the columns of the
 input matrix, using  
PearsonsCorrelation.correlation(double[], double[]). | 
protected RealMatrix | 
Covariance.computeCovarianceMatrix(RealMatrix matrix)
Create a covariance matrix from a matrix whose columns represent
 covariates. 
 | 
protected RealMatrix | 
Covariance.computeCovarianceMatrix(RealMatrix matrix,
                       boolean biasCorrected)
Compute a covariance matrix from a matrix whose columns represent covariates. 
 | 
RealMatrix | 
PearsonsCorrelation.covarianceToCorrelation(RealMatrix covarianceMatrix)
Derives a correlation matrix from a covariance matrix. 
 | 
| Constructor and Description | 
|---|
Covariance(RealMatrix matrix)
Create a covariance matrix from a matrix whose columns
 represent covariates. 
 | 
Covariance(RealMatrix matrix,
          boolean biasCorrected)
Create a covariance matrix from a matrix whose columns
 represent covariates. 
 | 
KendallsCorrelation(RealMatrix matrix)
Create a KendallsCorrelation from a RealMatrix whose columns
 represent variables to be correlated. 
 | 
PearsonsCorrelation(RealMatrix matrix)
Create a PearsonsCorrelation from a RealMatrix whose columns
 represent variables to be correlated. 
 | 
PearsonsCorrelation(RealMatrix covarianceMatrix,
                   int numberOfObservations)
Create a PearsonsCorrelation from a covariance matrix. 
 | 
SpearmansCorrelation(RealMatrix dataMatrix)
Create a SpearmansCorrelation from the given data matrix. 
 | 
SpearmansCorrelation(RealMatrix dataMatrix,
                    RankingAlgorithm rankingAlgorithm)
Create a SpearmansCorrelation with the given input data matrix
 and ranking algorithm. 
 | 
| Modifier and Type | Method and Description | 
|---|---|
RealMatrix | 
StatisticalMultivariateSummary.getCovariance()
Returns the covariance of the available values. 
 | 
RealMatrix | 
MultivariateSummaryStatistics.getCovariance()
Returns the covariance of the available values. 
 | 
| Modifier and Type | Method and Description | 
|---|---|
RealMatrix | 
VectorialCovariance.getResult()
Get the covariance matrix. 
 | 
| Modifier and Type | Method and Description | 
|---|---|
protected RealMatrix | 
GLSMultipleLinearRegression.calculateBetaVariance()
Calculates the variance on the beta. 
 | 
protected RealMatrix | 
OLSMultipleLinearRegression.calculateBetaVariance()
Calculates the variance-covariance matrix of the regression parameters. 
 | 
protected abstract RealMatrix | 
AbstractMultipleLinearRegression.calculateBetaVariance()
Calculates the beta variance of multiple linear regression in matrix
 notation. 
 | 
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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