Uses of Class
com.irurueta.algebra.Matrix

Packages that use Matrix

Package	Description
com.irurueta.algebra	This package contains classes related to algebra, such as Matrix class to contains matrices data and simple operations or Complex to handle computations with Complex numbers.
com.irurueta.statistics

Uses of Matrix in com.irurueta.algebra

Fields in com.irurueta.algebra declared as Matrix

Modifier and Type	Field	Description
protected Matrix	Decomposer.inputMatrix	Reference to input matrix to be decomposed.
private Matrix	LUDecomposer.lu	Internal matrix containing results of decomposition.
private Matrix	QRDecomposer.q	Internal matrix containing Q factor.
private Matrix	EconomyQRDecomposer.qr	Internal matrix containing results of decomposition.
private Matrix	CholeskyDecomposer.r	Internal storage of Cholesky decomposition for provided input matrix.
private Matrix	QRDecomposer.r	Internal matrix containing R factor.
private Matrix	SingularValueDecomposer.u	Internal storage of U.
private Matrix	SingularValueDecomposer.v	Internal storage of V.

Methods in com.irurueta.algebra that return Matrix

Modifier and Type	Method	Description
Matrix	Matrix.addAndReturnNew(Matrix other)	Adds provided matrix to this instance and returns the result as a new matrix instance.
Matrix	Matrix.clone()	Returns a new matrix instance containing the same data as this instance.
static Matrix	Matrix.createWithGaussianRandomValues(int rows, int columns, double mean, double standardDeviation)	Creates new matrix instance using provided size and containing gaussian/normal distributed random values with provided median and standard deviation.
static Matrix	Matrix.createWithGaussianRandomValues(int rows, int columns, double mean, double standardDeviation, Random random)	Creates new matrix instance using provided size and containing gaussian/normal distributed random values with provided median and standard deviation and using provided random generator
static Matrix	Matrix.createWithUniformRandomValues(int rows, int columns, double minValue, double maxValue)	Creates new matrix instance using provided size and containing uniformly distributed random values with provided range.
static Matrix	Matrix.createWithUniformRandomValues(int rows, int columns, double minValue, double maxValue, Random random)	Creates new matrix instance using provided size and containing uniformly distributed random values with provided range and using provided random generator
static Matrix	Utils.crossProduct(double[] v, Matrix m)	Computes the cross product of one vector of length 3 and N vectors of length 3.
static Matrix	Matrix.diagonal(double[] diagonal)	Creates a diagonal matrix having all the elements in provided array in its diagonal and the remaining elements equal to zero.
Matrix	Matrix.elementByElementProductAndReturnNew(Matrix other)	Computes element by element product (i.e.
Matrix	EconomyQRDecomposer.getH()	Returns the Householder vectors.
Matrix	Decomposer.getInputMatrix()	Returns a reference to input matrix to be decomposed.
Matrix	CholeskyDecomposer.getL()	Returns Cholesky matrix factor corresponding to a Lower triangular matrix following this expression: A = L * L'.
Matrix	LUDecomposer.getL()	Returns a new matrix instance containing the pivot corrected Lower triangular matrix resulting from LU decomposition for provided input matrix.
Matrix	SingularValueDecomposer.getNullspace()	Returns matrix containing null-space of provided input matrix, which spans a subspace of dimension equal to the nullity of input matrix.
Matrix	SingularValueDecomposer.getNullspace(double singularValueThreshold)	Returns matrix containing null-space of provided input matrix, which spans a subspace of dimension equal to the nullity of input matrix.
Matrix	LUDecomposer.getPivottedL()	Returns a new matrix instance containing the Lower triangular matrix resulting from LU decomposition before correcting any possible pivots.
Matrix	EconomyQRDecomposer.getQ()	Return the economy-sized orthogonal factor matrix.
Matrix	QRDecomposer.getQ()	Returns the economy-sized orthogonal factor matrix.
Matrix	RQDecomposer.getQ()	Returns the economy-sized orthogonal factor matrix.
Matrix	CholeskyDecomposer.getR()	Returns Cholesky matrix factor corresponding to an upper triangular matrix following this expression: A = R' * R.
Matrix	EconomyQRDecomposer.getR()	Return upper triangular factor matrix.
Matrix	QRDecomposer.getR()	Returns upper triangular factor matrix.
Matrix	RQDecomposer.getR()	Returns upper triangular factor matrix.
Matrix	SingularValueDecomposer.getRange()	Return matrix containing Range space of provided input matrix, which spans a subspace of dimension equal to the rank of input matrix.
Matrix	SingularValueDecomposer.getRange(double singularValueThreshold)	Returns matrix containing Range space of provided input matrix, which spans a subspace of dimension equal to the rank of input matrix.
Matrix	Matrix.getSubmatrix(int topLeftRow, int topLeftColumn, int bottomRightRow, int bottomRightColumn)	Obtains a sub-matrix of current matrix instance.
Matrix	LUDecomposer.getU()	Returns a new matrix instance containing the Upper triangular matrix resulting from LU decomposition for provided input matrix.
Matrix	SingularValueDecomposer.getU()	Returns a new matrix instance containing the left singular vector (U factor) from Singular Value matrix decomposition, which consists on decomposing a matrix using the following expression: A = U * S * V'.
Matrix	SingularValueDecomposer.getV()	Returns a new matrix instance containing the right singular vectors (V factor) from Singular Value matrix decomposition, which consists on decomposing a matrix using the following expression: A = U * S * V', Where A is provided input matrix of size m-by-n and V' denotes the transpose/conjugate of V, which is an n-by-n unary matrix for m < n.
Matrix	SingularValueDecomposer.getW()	Returns a new diagonal matrix instance containing all singular values on its diagonal after Singular Value matrix decomposition, which consists on decomposing a matrix using the following expression: A = U * S * V'.
static Matrix	Matrix.identity(int rows, int columns)	Creates and returns a new matrix instance having all the elements on the diagonal equal to one and the remaining ones equal to zero.
static Matrix	Utils.inverse(double[] array)	Computes array pseudo-inverse considering it as a column matrix.
static Matrix	Utils.inverse(Matrix m)	Computes matrix inverse if provided matrix is squared, or pseudo-inverse otherwise.
Matrix	Matrix.multiplyAndReturnNew(Matrix other)	Multiplies this matrix with provided matrix and returns the result as a new instance.
Matrix	Matrix.multiplyByScalarAndReturnNew(double scalar)	Computes product by scalar of this instance multiplying all its elements by provided scalar value and returning the result as a new instance.
Matrix	Matrix.multiplyKroneckerAndReturnNew(Matrix other)	Computes the Kronecker product with provided matrix and returns the result as a new instance.
static Matrix	Matrix.newFromArray(double[] array)	Instantiates new matrix from array using DEFAULT_USE_COLUMN_ORDER
static Matrix	Matrix.newFromArray(double[] array, boolean isColumnOrder)	Instantiates new matrix from array using either column or row order
static Matrix	Utils.pseudoInverse(double[] array)	Computes Moore-Penrose pseudo-inverse of provided array considering it as a column matrix.
static Matrix	Utils.pseudoInverse(Matrix m)	Computes Moore-Penrose pseudo-inverse of provided matrix.
static Matrix	Utils.schurcAndReturnNew(Matrix m, int pos)	Computes the Schur complement of the sub-matrix A within a symmetric matrix, returning always the full Schur complement.
static Matrix	Utils.schurcAndReturnNew(Matrix m, int pos, boolean fromStart)	Computes the Schur complement of a symmetric matrix, returning always the full Schur complement.
static Matrix	Utils.schurcAndReturnNew(Matrix m, int pos, boolean fromStart, boolean sqrt)	Computes the Schur complement of a symmetric matrix.
static Matrix	Utils.schurcAndReturnNew(Matrix m, int pos, boolean fromStart, boolean sqrt, Matrix iA)	Computes the Schur complement of a symmetric matrix.
static Matrix	Utils.schurcAndReturnNew(Matrix m, int pos, boolean fromStart, Matrix iA)	Computes the Schur complement of a symmetric matrix, returning always the full Schur complement.
static Matrix	Utils.schurcAndReturnNew(Matrix m, int pos, Matrix iA)	Computes the Schur complement of the sub-matrix A within a symmetric matrix, returning always the full Schur complement.
static Matrix	Utils.skewMatrix(double[] array)	Computes the skew-symmetric matrix of provided vector of length 3.
static Matrix	Utils.skewMatrix(Matrix m)	Computes the skew-symmetric matrix of provided matrix of size 3x1 or 13.
Matrix	CholeskyDecomposer.solve(Matrix b)	Solves a linear system of equations of the following form: A * X = B.
Matrix	EconomyQRDecomposer.solve(Matrix b)	Solves a linear system of equations of the following form: A * X = B, where A is the input matrix provided for QR decomposition, X is the solution to the system of equations, and B is the parameters vector/matrix.
Matrix	EconomyQRDecomposer.solve(Matrix b, double roundingError)	Solves a linear system of equations of the following form: A * X = B, where A is the input matrix provided for QR decomposition, X is the solution to the system of equations, and B is the parameters vector/matrix.
Matrix	LUDecomposer.solve(Matrix b)	Solves a linear system of equations of the following form: A * X = B.
Matrix	LUDecomposer.solve(Matrix b, double roundingError)	Solves a linear system of equations of the following form: A * X = B.
Matrix	QRDecomposer.solve(Matrix b)	Solves a linear system of equations of the following form: A * X = B.
Matrix	QRDecomposer.solve(Matrix b, double roundingError)	Solves a linear system of equations of the following form: A * X = B.
Matrix	SingularValueDecomposer.solve(Matrix b)	Solves a linear system of equations of the following form: A * X = B using the pseudo-inverse to find the least squares solution.
Matrix	SingularValueDecomposer.solve(Matrix b, double singularValueThreshold)	Solves a linear system of equations of the following form: A * X = B using the pseudo-inverse to find the least squares solution.
static Matrix	Utils.solve(Matrix m, Matrix b)	Solves a linear system of equations of the form: m * x = b.
Matrix	Matrix.subtractAndReturnNew(Matrix other)	Subtracts provided matrix from this instance and returns the result as a new matrix instance.
Matrix	Matrix.symmetrizeAndReturnNew()	Symmetrizes this instance and returns the result as a new matrix instance.
Matrix	Matrix.transposeAndReturnNew()	Transposes current matrix and returns result as a new instance.

Methods in com.irurueta.algebra with parameters of type Matrix

Modifier and Type	Method	Description
void	Matrix.add(Matrix other)	Adds provided matrix to this instance.
void	Matrix.add(Matrix other, Matrix result)	Adds another matrix to this matrix instance and stores the result in provided result matrix.
Matrix	Matrix.addAndReturnNew(Matrix other)	Adds provided matrix to this instance and returns the result as a new matrix instance.
static double	Utils.cond(Matrix m)	Computes condition number of provided matrix.
void	Matrix.copyFrom(Matrix input)	Copies the contents of provided matrix into this instance.
void	Matrix.copyTo(Matrix output)	Copies this matrix data into provided matrix.
static void	Utils.crossProduct(double[] v1, double[] v2, double[] result, Matrix jacobian1, Matrix jacobian2)	Computes the cross product of two vectors of length 3 The cross product of two vectors a and b is denoted as 'axb' or 'a^b', resulting in a perpendicular vector to both a and b vectors.
static double[]	Utils.crossProduct(double[] v1, double[] v2, Matrix jacobian1, Matrix jacobian2)	Computes the cross product of two vectors of length 3 The cross product of two vectors a and b is denoted as 'axb' or 'a^b', resulting in a perpendicular vector to both a and b vectors.
static Matrix	Utils.crossProduct(double[] v, Matrix m)	Computes the cross product of one vector of length 3 and N vectors of length 3.
static void	Utils.crossProduct(double[] v, Matrix m, Matrix result)	Computes the cross product of one vector of length 3 and N vectors of length 3.
static double	Utils.det(Matrix m)	Computes determinant of provided matrix.
static void	Matrix.diagonal(double[] diagonal, Matrix result)	Makes provided result matrix a diagonal matrix containing provided elements in the diagonal.
static double	ArrayUtils.dotProduct(double[] firstOperand, double[] secondOperand, Matrix jacobianFirst, Matrix jacobianSecond)	Computes the dot product of provided arrays as the sum of the product of the elements of both arrays.
static double	Utils.dotProduct(double[] firstOperand, double[] secondOperand, Matrix jacobianFirst, Matrix jacobianSecond)	Computes the dot product of provided arrays as the sum of the product of the elements of both arrays.
static double	Utils.dotProduct(Matrix firstOperand, Matrix secondOperand)	Computes the dot product of provided matrices, as the sum of the product of the elements on both matrices, assuming that both represent column vectors.
static double	Utils.dotProduct(Matrix firstOperand, Matrix secondOperand, Matrix jacobianFirst, Matrix jacobianSecond)	Computes the dot product of provided matrices, as the sum of the product of the elements on both matrices, assuming that both represent column vectors.
void	Matrix.elementByElementProduct(Matrix other)	Computes element by element product (i.e.
void	Matrix.elementByElementProduct(Matrix other, Matrix result)	Computes element by element product (i.e.
Matrix	Matrix.elementByElementProductAndReturnNew(Matrix other)	Computes element by element product (i.e.
boolean	Matrix.equals(Matrix other)	Checks if provided matrix has exactly the same contents as this matrix instance.
boolean	Matrix.equals(Matrix other, double threshold)	Checks if provided matrix has contents similar to this matrix by checking that all values have a maximum difference equal to provided threshold and same size.
static void	Matrix.fillWithGaussianRandomValues(double mean, double standardDeviation, Matrix result)	Fills provided matrix with random Gaussian values with provided mean and standard deviation
static void	Matrix.fillWithGaussianRandomValues(double mean, double standardDeviation, Random random, Matrix result)	Fills provided matrix with random Gaussian values with provided mean and standard deviation.
static void	Matrix.fillWithUniformRandomValues(double minValue, double maxValue, Matrix result)	Fills provided matrix with random uniform values ranging from minValue to maxValue.
static void	Matrix.fillWithUniformRandomValues(double minValue, double maxValue, Random random, Matrix result)	Fills provided matrix with random uniform values ranging from minValue to maxValue.
void	EconomyQRDecomposer.getH(Matrix h)	Computes the Householder vectors and store them in provided matrix.
void	LUDecomposer.getL(Matrix l)	Fills provided matrix instance with the pivot corrected Lower triangular matrix resulting from LU decomposition for provided input matrix.
double	FrobeniusNormComputer.getNorm(Matrix m)	Computes norm of provided matrix.
double	InfinityNormComputer.getNorm(Matrix m)	Computes norm of provided matrix.
double	NormComputer.getNorm(double[] array, Matrix jacobian)	Computes norm of provided array and stores the jacobian into provided instance.
abstract double	NormComputer.getNorm(Matrix m)	Computes norm of provided matrix.
double	OneNormComputer.getNorm(Matrix m)	Computes norm of provided matrix.
void	SingularValueDecomposer.getNullspace(double singularValueThreshold, Matrix nullspace)	Sets into provided matrix null-space of provided input matrix, which spans a subspace of dimension equal to the nullity of input matrix.
void	SingularValueDecomposer.getNullspace(Matrix nullspace)	Sets into provided matrix null-space of provided input matrix, which spans a subspace of dimension equal to the nullity of input matrix.
void	LUDecomposer.getPivottedL(Matrix pivottedL)	Fills provided matrix instance with the Lower triangular matrix resulting from LU decomposition before correcting any possible pivots.
void	EconomyQRDecomposer.getQ(Matrix q)	Computes the economy-sized orthogonal factor matrix and stores it into provided matrix.
void	EconomyQRDecomposer.getR(Matrix r)	Computes upper triangular factor matrix and stores it into provided matrix.
void	SingularValueDecomposer.getRange(double singularValueThreshold, Matrix range)	Sets into provided range matrix the Range space of provided input matrix, which spans a subspace of dimension equal to the rank of input matrix.
void	SingularValueDecomposer.getRange(Matrix range)	Sets into provided range matrix the Range space of provided input matrix, which spans a subspace of dimension equal to the rank of input matrix.
void	Matrix.getSubmatrix(int topLeftRow, int topLeftColumn, int bottomRightRow, int bottomRightColumn, Matrix result)	Obtains a sub-matrix of current matrix instance.
void	LUDecomposer.getU(Matrix u)	Fills provided matrix instance with the Upper triangular matrix resulting from LU decomposition for provided input matrix.
void	SingularValueDecomposer.getW(Matrix m)	Copies diagonal matrix into provided instance containing all singular values on its diagonal after Singular Value matrix decomposition, which consists on decomposing a matrix using the following expression: A = U * S * V'.
static void	Matrix.identity(Matrix m)	Sets values into provided matrix to make it an identity matrix (all elements in the diagonal equal to one, and remaining elements to zero).
private void	Matrix.internalAdd(Matrix other, Matrix result)	Method to internally add two matrices.
private void	Matrix.internalElementByElementProduct(Matrix other, Matrix result)	Method to internally compute element by element product of two matrices.
private void	SingularValueDecomposer.internalGetNullspace(int nullity, double singularValueThreshold, Matrix nullspace)	Internal method to copy null-space vector values into provided matrix.
private void	SingularValueDecomposer.internalGetRange(int rank, double singularValueThreshold, Matrix range)	Internal method to copy range space vector values into provided matrix.
private void	Matrix.internalGetSubmatrix(int topLeftRow, int topLeftColumn, int bottomRightRow, int bottomRightColumn, Matrix result)	Internal method to retrieve a sub-matrix of current matrix instance.
private void	Matrix.internalMultiply(Matrix other, double[] resultBuffer, int[] resultColumnIndex)	Method to internally multiply two matrices.
private void	Matrix.internalMultiply(Matrix other, Matrix result)	Method to internally multiply two matrices.
private void	Matrix.internalMultiplyKronecker(Matrix other, double[] resultBuffer, int[] resultColumnIndex)	Method to internally compute the Kronecker product between two matrices.
private void	Matrix.internalMultiplyKronecker(Matrix other, Matrix result)	Method to internally compute the Kronecker product between two matrices.
private static void	Utils.internalSkewMatrix(Matrix m, Matrix result, boolean columnwise)	Internal method to compute skew matrix
private void	Matrix.internalSubtract(Matrix other, Matrix result)	Method to internally subtract two matrices.
private void	Matrix.internalTranspose(Matrix result)	Method to internally compute matrix transposition.
static void	GaussJordanElimination.inverse(Matrix a)	Computes inverse of matrix "a".
static void	Utils.inverse(double[] array, Matrix result)	Computes array pseudo-inverse considering it as a column matrix and stores the result in provided result matrix.
static Matrix	Utils.inverse(Matrix m)	Computes matrix inverse if provided matrix is squared, or pseudo-inverse otherwise.
static void	Utils.inverse(Matrix m, Matrix result)	Computes matrix inverse if provided matrix is squared, or pseudo-inverse otherwise and stores the result in provided result matrix.
static boolean	Utils.isOrthogonal(Matrix m)	Checks if the matrix is orthogonal (its transpose is its inverse).
static boolean	Utils.isOrthogonal(Matrix m, double threshold)	Checks if the matrix is orthogonal (its transpose is its inverse).
static boolean	Utils.isOrthonormal(Matrix m)	Checks if the matrix is orthonormal up to DEFAULT_ORTHOGONAL_THRESHOLD (it is orthogonal and its Frobenius norm is one)
static boolean	Utils.isOrthonormal(Matrix m, double threshold)	Checks if the matrix is orthonormal (it is orthogonal and its Frobenius norm is one)
static boolean	Utils.isSymmetric(Matrix m)	Check if the matrix is symmetric.
static boolean	Utils.isSymmetric(Matrix m, double threshold)	Check if the matrix is symmetric.
void	Matrix.multiply(Matrix other)	Multiplies this matrix with provided matrix.
void	Matrix.multiply(Matrix other, Matrix result)	Multiplies another matrix to this matrix instance and stores the result in provided result matrix.
Matrix	Matrix.multiplyAndReturnNew(Matrix other)	Multiplies this matrix with provided matrix and returns the result as a new instance.
private void	Matrix.multiplyByScalar(double scalar, Matrix result)	Computes product by scalar of this instance multiplying all its elements by provided scalar value and storing the results in provided result matrix.
void	Matrix.multiplyKronecker(Matrix other)	Computes the Kronecker product of this matrix with provided matrix and updates this matrix with the result of the multiplication.
void	Matrix.multiplyKronecker(Matrix other, Matrix result)	Computes the Kronecker product with provided matrix and stores the result in provided result matrix.
Matrix	Matrix.multiplyKroneckerAndReturnNew(Matrix other)	Computes the Kronecker product with provided matrix and returns the result as a new instance.
static double	FrobeniusNormComputer.norm(double[] array, Matrix jacobian)	Computes norm of provided array and stores the jacobian into provided instance.
static double	FrobeniusNormComputer.norm(Matrix m)	Computes norm of provided matrix.
static double	InfinityNormComputer.norm(double[] array, Matrix jacobian)	Computes norm of provided array and stores the jacobian into provided instance.
static double	InfinityNormComputer.norm(Matrix m)	Computes norm of provided matrix.
static double	OneNormComputer.norm(double[] array, Matrix jacobian)	Computes norm of provided array and stores the jacobian into provided instance.
static double	OneNormComputer.norm(Matrix m)	Computes norm of provided matrix.
static double	Utils.norm1(Matrix m)	Computes one norm of provided input matrix.
static double	Utils.norm2(Matrix m)	Computes two norm of provided input matrix.
static void	ArrayUtils.normalize(double[] v, double[] result, Matrix jacobian)	Normalizes provided array and computes corresponding jacobian.
static void	ArrayUtils.normalize(double[] v, Matrix jacobian)	Normalizes provided array, updates its values and computes corresponding jacobian.
static double[]	ArrayUtils.normalizeAndReturnNew(double[] v, Matrix jacobian)	Normalizes provided array and computes corresponding jacobian.
static double	Utils.normF(Matrix m)	Computes Frobenius norm of provided input matrix.
static double	Utils.normInf(Matrix m)	Computes infinity norm of provided input matrix.
static void	GaussJordanElimination.process(Matrix a, double[] b)	Computes Gauss-Jordan elimination by attempting to solve linear system of equations a * x = b.
static void	GaussJordanElimination.process(Matrix a, Matrix b)	Computes Gauss-Jordan elimination by attempting to solve linear system of equations a * x = b.
static Matrix	Utils.pseudoInverse(Matrix m)	Computes Moore-Penrose pseudo-inverse of provided matrix.
static int	Utils.rank(Matrix m)	Computes rank of provided matrix.
static void	Utils.schurc(Matrix m, int pos, boolean fromStart, boolean sqrt, Matrix result)	Computes the Schur complement of a symmetric matrix.
static void	Utils.schurc(Matrix m, int pos, boolean fromStart, boolean sqrt, Matrix result, Matrix iA)	Computes the Schur complement of a symmetric matrix.
static void	Utils.schurc(Matrix m, int pos, boolean fromStart, Matrix result)	Computes the Schur complement of a symmetric matrix, returning always the full Schur complement.
static void	Utils.schurc(Matrix m, int pos, boolean fromStart, Matrix result, Matrix iA)	Computes the Schur complement of a symmetric matrix, returning always the full Schur complement.
static void	Utils.schurc(Matrix m, int pos, Matrix result)	Computes the Schur complement of the sub-matrix A within a symmetric matrix, returning always the full Schur complement.
static void	Utils.schurc(Matrix m, int pos, Matrix result, Matrix iA)	Computes the Schur complement of the sub-matrix A within a symmetric matrix, returning always the full Schur complement.
static Matrix	Utils.schurcAndReturnNew(Matrix m, int pos)	Computes the Schur complement of the sub-matrix A within a symmetric matrix, returning always the full Schur complement.
static Matrix	Utils.schurcAndReturnNew(Matrix m, int pos, boolean fromStart)	Computes the Schur complement of a symmetric matrix, returning always the full Schur complement.
static Matrix	Utils.schurcAndReturnNew(Matrix m, int pos, boolean fromStart, boolean sqrt)	Computes the Schur complement of a symmetric matrix.
static Matrix	Utils.schurcAndReturnNew(Matrix m, int pos, boolean fromStart, boolean sqrt, Matrix iA)	Computes the Schur complement of a symmetric matrix.
static Matrix	Utils.schurcAndReturnNew(Matrix m, int pos, boolean fromStart, Matrix iA)	Computes the Schur complement of a symmetric matrix, returning always the full Schur complement.
static Matrix	Utils.schurcAndReturnNew(Matrix m, int pos, Matrix iA)	Computes the Schur complement of the sub-matrix A within a symmetric matrix, returning always the full Schur complement.
void	CholeskyDecomposer.setInputMatrix(Matrix inputMatrix)	Sets reference to input matrix to be decomposed.
void	Decomposer.setInputMatrix(Matrix inputMatrix)	Sets reference to input matrix to be decomposed.
void	EconomyQRDecomposer.setInputMatrix(Matrix inputMatrix)	Sets reference to input matrix to be decomposed.
void	LUDecomposer.setInputMatrix(Matrix inputMatrix)	Sets reference to input matrix to be decomposed.
void	QRDecomposer.setInputMatrix(Matrix inputMatrix)	Sets reference to input matrix to be decomposed.
void	RQDecomposer.setInputMatrix(Matrix inputMatrix)	Sets reference to input matrix to be decomposed.
void	SingularValueDecomposer.setInputMatrix(Matrix inputMatrix)	Sets reference to input matrix to be decomposed.
void	Matrix.setSubmatrix(int topLeftRow, int topLeftColumn, int bottomRightRow, int bottomRightColumn, Matrix submatrix)	Copies elements from provided sub-matrix into this matrix at provided location.
void	Matrix.setSubmatrix(int topLeftRow, int topLeftColumn, int bottomRightRow, int bottomRightColumn, Matrix submatrix, int submatrixTopLeftRow, int submatrixTopLeftColumn, int submatrixBottomRightRow, int submatrixBottomRightColumn)	Copies elements from provided sub-matrix into this matrix at provided location
static void	Utils.skewMatrix(double[] array, Matrix result)	Computes the skew-symmetric matrix of provided vector of length 3 and stores the result in provided matrix.
static void	Utils.skewMatrix(double[] array, Matrix result, Matrix jacobian)	Computes the skew-symmetric matrix of provided vector of length 3 and stores the result in provided matrix.
static Matrix	Utils.skewMatrix(Matrix m)	Computes the skew-symmetric matrix of provided matrix of size 3x1 or 13.
static void	Utils.skewMatrix(Matrix m, Matrix result)	Computes the skew-symmetric matrix of provided matrix of size 3x1 or 13.
static void	Utils.skewMatrix(Matrix m, Matrix result, Matrix jacobian)	Computes the skew-symmetric matrix of provided matrix of size 3x1 or 13.
Matrix	CholeskyDecomposer.solve(Matrix b)	Solves a linear system of equations of the following form: A * X = B.
void	CholeskyDecomposer.solve(Matrix b, Matrix result)	Solves a linear system of equations of the following form: A * X = B.
Matrix	EconomyQRDecomposer.solve(Matrix b)	Solves a linear system of equations of the following form: A * X = B, where A is the input matrix provided for QR decomposition, X is the solution to the system of equations, and B is the parameters vector/matrix.
Matrix	EconomyQRDecomposer.solve(Matrix b, double roundingError)	Solves a linear system of equations of the following form: A * X = B, where A is the input matrix provided for QR decomposition, X is the solution to the system of equations, and B is the parameters vector/matrix.
void	EconomyQRDecomposer.solve(Matrix b, double roundingError, Matrix result)	Solves a linear system of equations of the following form: A * X = B, where A is the input matrix provided for QR decomposition, X is the solution to the system of equations, and B is the parameters vector/matrix.
void	EconomyQRDecomposer.solve(Matrix b, Matrix result)	Solves a linear system of equations of the following form: A * X = B, where A is the input matrix provided for QR decomposition, X is the solution to the system of equations, and B is the parameters vector/matrix.
Matrix	LUDecomposer.solve(Matrix b)	Solves a linear system of equations of the following form: A * X = B.
Matrix	LUDecomposer.solve(Matrix b, double roundingError)	Solves a linear system of equations of the following form: A * X = B.
void	LUDecomposer.solve(Matrix b, double roundingError, Matrix result)	Solves a linear system of equations of the following form: A * X = B.
void	LUDecomposer.solve(Matrix b, Matrix result)	Solves a linear system of equations of the following form: A * X = B.
Matrix	QRDecomposer.solve(Matrix b)	Solves a linear system of equations of the following form: A * X = B.
Matrix	QRDecomposer.solve(Matrix b, double roundingError)	Solves a linear system of equations of the following form: A * X = B.
void	QRDecomposer.solve(Matrix b, double roundingError, Matrix result)	Solves a linear system of equations of the following form: A * X = B.
void	QRDecomposer.solve(Matrix b, Matrix result)	Solves a linear system of equations of the following form: A * X = B.
Matrix	SingularValueDecomposer.solve(Matrix b)	Solves a linear system of equations of the following form: A * X = B using the pseudo-inverse to find the least squares solution.
Matrix	SingularValueDecomposer.solve(Matrix b, double singularValueThreshold)	Solves a linear system of equations of the following form: A * X = B using the pseudo-inverse to find the least squares solution.
void	SingularValueDecomposer.solve(Matrix b, double singularValueThreshold, Matrix result)	Solves a linear system of equations of the following form: A * X = B using the pseudo-inverse to find the least squares solution.
void	SingularValueDecomposer.solve(Matrix b, Matrix result)	Solves a linear system of equations of the following form: A * X = B using the pseudo-inverse to find the least squares solution.
static double[]	Utils.solve(Matrix m, double[] b)	Solves a linear system of equations of the form: m * x = b.
static void	Utils.solve(Matrix m, double[] b, double[] result)	Solves a linear system of equations of the form m * x = b, where b is assumed to be the parameters column vector, x is the returned matrix containing the solution and m is the matrix of the linear system of equations.
static Matrix	Utils.solve(Matrix m, Matrix b)	Solves a linear system of equations of the form: m * x = b.
static void	Utils.solve(Matrix m, Matrix b, Matrix result)	Solves a linear system of equations of the form: m * x = b.
void	Matrix.subtract(Matrix other)	Subtracts provided matrix from this instance.
void	Matrix.subtract(Matrix other, Matrix result)	Subtracts another matrix from this matrix instance and stores the result in provided result matrix.
Matrix	Matrix.subtractAndReturnNew(Matrix other)	Subtracts provided matrix from this instance and returns the result as a new matrix instance.
void	Matrix.symmetrize(Matrix result)	Symmetrizes this instance and stores the result into provided instance.
static double	Utils.trace(Matrix m)	Computes trace of provided matrix.
void	Matrix.transpose(Matrix result)	Transposes current matrix and stores result in provided matrix.

Constructors in com.irurueta.algebra with parameters of type Matrix

Modifier	Constructor	Description
	CholeskyDecomposer(Matrix inputMatrix)	Constructor of this class.
protected	Decomposer(Matrix inputMatrix)	Constructor of this class.
	EconomyQRDecomposer(Matrix inputMatrix)	Constructor of this class.
	LUDecomposer(Matrix inputMatrix)	Constructor of this class.
	Matrix(Matrix m)	Copy constructor.
	QRDecomposer(Matrix inputMatrix)	Constructor of this class.
	RQDecomposer(Matrix inputMatrix)	Constructor of this class.
	SingularValueDecomposer(Matrix inputMatrix)	Constructor of this class.
	SingularValueDecomposer(Matrix inputMatrix, int maxIters)	Constructor of this class.

Uses of Matrix in com.irurueta.statistics

Fields in com.irurueta.statistics declared as Matrix

Modifier and Type	Field	Description
private Matrix	MultivariateNormalDist.cov	Covariance of Gaussian distribution.
private Matrix	MultivariateGaussianRandomizer.covariance	Covariance matrix.
private Matrix	MultivariateNormalDist.covBasis	Basis in which the covariance matrix is expressed.
private Matrix	MultivariateGaussianRandomizer.l	Lower triangular Cholesky decomposition of covariance matrix.

Methods in com.irurueta.statistics that return Matrix

Modifier and Type	Method	Description
Matrix	MultivariateGaussianRandomizer.getCovariance()	Returns covariance to be used for Gaussian random value generation.
Matrix	MultivariateNormalDist.getCovariance()	Gets matrix containing covariance of this multivariate Gaussian distribution.
Matrix	MultivariateNormalDist.getCovarianceBasis()	Basis containing on each column the direction of each variance in the multidimensional Gaussian distribution, which is obtained from provided covariance matrix.

Methods in com.irurueta.statistics with parameters of type Matrix

Modifier and Type	Method	Description
double	MultivariateNormalDist.cdf(double[] x, Matrix basis)	Evaluates the cumulative distribution function (c.d.f.) of a Gaussian distribution having current mean and covariance values.
void	MultivariateNormalDist.JacobianEvaluator.evaluate(double[] x, double[] y, Matrix jacobian)	Evaluates multivariate point
void	MultivariateNormalDist.getCovariance(Matrix result)	Gets matrix containing covariance of this multivariate Gaussian distribution.
void	MultivariateNormalDist.invcdf(double[] p, double[] result, Matrix basis)	Evaluates the inverse cumulative distribution function of a multivariate Gaussian distribution for current mean and covariance values and provided probability values for each dimension of the multivariate Gaussian distribution.
double[]	MultivariateNormalDist.invcdf(double[] p, Matrix basis)	Evaluates the inverse cumulative distribution function of a multivariate Gaussian distribution for current mean and covariance values and provided probability values for each dimension of the multivariate Gaussian distribution.
void	MultivariateNormalDist.invcdf(double p, double[] result, Matrix basis)	Evaluates the inverse cumulative distribution function of a multivariate Gaussian distribution for current mean and covariance values and provided probability value.
double[]	MultivariateNormalDist.invcdf(double p, Matrix basis)	Evaluates the inverse cumulative distribution function of a multivariate Gaussian distribution for current mean and covariance values and provided probability value.
static boolean	MultivariateNormalDist.isValidCovariance(Matrix cov)	Indicates whether provided matrix is a valid covariance matrix.
static MultivariateNormalDist	MultivariateNormalDist.propagate(MultivariateNormalDist.JacobianEvaluator evaluator, double[] mean, Matrix covariance)	Evaluates the Jacobian and a multivariate function at a certain mean point and computes the non-linear propagation of Gaussian uncertainty through such function at such point.
static void	MultivariateNormalDist.propagate(MultivariateNormalDist.JacobianEvaluator evaluator, double[] mean, Matrix covariance, MultivariateNormalDist result)	Evaluates the Jacobian and a multivariate function at a certain mean point and computes the non-linear propagation of Gaussian uncertainty through such function at such point.
void	MultivariateNormalDist.setCovariance(Matrix cov)	Sets covariance of this multivariate Gaussian distribution.
void	MultivariateNormalDist.setCovariance(Matrix cov, boolean validateSymmetricPositiveDefinite)	Sets covariance of this multivariate Gaussian distribution.
final void	MultivariateGaussianRandomizer.setMeanAndCovariance(double[] mean, Matrix covariance)	Sets mean and covariance to generate multivariate Gaussian random values.
final void	MultivariateNormalDist.setMeanAndCovariance(double[] mu, Matrix cov)	Sets mean and covariance of this multivariate Gaussian distribution.
final void	MultivariateNormalDist.setMeanAndCovariance(double[] mu, Matrix cov, boolean validateSymmetricPositiveDefinite)	Sets mean and covariance of this multivariate Gaussian distribution.

Constructors in com.irurueta.statistics with parameters of type Matrix

Modifier	Constructor	Description
	MultivariateGaussianRandomizer(double[] mean, Matrix covariance)	Constructor.
	MultivariateGaussianRandomizer(Random internalRandom, double[] mean, Matrix covariance)	Constructor.
	MultivariateNormalDist(double[] mean, Matrix covariance)	Constructor.
	MultivariateNormalDist(double[] mean, Matrix covariance, boolean validateSymmetricPositiveDefinite)	Constructor.