Uses of Class
com.irurueta.algebra.NotAvailableException

Packages that use NotAvailableException

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 NotAvailableException in com.irurueta.algebra

Methods in com.irurueta.algebra that throw NotAvailableException

Modifier and Type	Method	Description
double	LUDecomposer.determinant()	Returns determinant of provided input matrix using LU decomposition as means to obtain it.
double	SingularValueDecomposer.getConditionNumber()	Returns the condition number of provided input matrix found after decomposition.
Matrix	EconomyQRDecomposer.getH()	Returns the Householder vectors.
void	EconomyQRDecomposer.getH(Matrix h)	Computes the Householder vectors and store them in provided matrix.
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.
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	SingularValueDecomposer.getNegligibleSingularValueThreshold()	Returns threshold to be used for determining whether a singular value is negligible or not.
double	SingularValueDecomposer.getNorm2()	Returns the 2-norm of provided input matrix, which is equal to the highest singular value found after decomposition.
int	SingularValueDecomposer.getNullity()	Returns effective numerical matrix nullity.
int	SingularValueDecomposer.getNullity(double singularValueThreshold)	Returns effective numerical matrix nullity.
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.
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.
int[]	LUDecomposer.getPivot()	Returns pivot permutation vector.
Matrix	LUDecomposer.getPivottedL()	Returns a new matrix instance containing the Lower triangular matrix resulting from LU decomposition before correcting any possible pivots.
void	LUDecomposer.getPivottedL(Matrix pivottedL)	Fills provided matrix instance with the Lower triangular matrix resulting from LU decomposition before correcting any possible pivots.
Matrix	EconomyQRDecomposer.getQ()	Return the economy-sized orthogonal factor matrix.
void	EconomyQRDecomposer.getQ(Matrix q)	Computes the economy-sized orthogonal factor matrix and stores it into provided 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.
void	EconomyQRDecomposer.getR(Matrix r)	Computes upper triangular factor matrix and stores it into provided 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.
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.
int	SingularValueDecomposer.getRank()	Returns effective numerical matrix rank.
int	SingularValueDecomposer.getRank(double singularValueThreshold)	Returns effective numerical matrix rank.
double	SingularValueDecomposer.getReciprocalConditionNumber()	Returns the inverse of the condition number, i.e. 1.0 / condition number.
double[]	SingularValueDecomposer.getSingularValues()	Returns a new vector instance containing all singular values after decomposition.
Matrix	LUDecomposer.getU()	Returns a new matrix instance containing the Upper triangular matrix resulting from LU decomposition for provided input matrix.
void	LUDecomposer.getU(Matrix u)	Fills provided matrix instance with 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'.
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'.
boolean	EconomyQRDecomposer.isFullRank()	Returns boolean indicating whether provided input matrix has full rank or not.
boolean	EconomyQRDecomposer.isFullRank(double roundingError)	Returns boolean indicating whether provided input matrix has full rank or not.
boolean	QRDecomposer.isFullRank()	Returns boolean indicating whether provided input matrix has full rank or not.
boolean	QRDecomposer.isFullRank(double roundingError)	Returns boolean indicating whether provided input matrix has full rank or not.
boolean	LUDecomposer.isSingular()	Return boolean indicating whether provided input matrix is singular or not after computing LU decomposition.
boolean	LUDecomposer.isSingular(double roundingError)	Return boolean indicating whether provided input matrix is singular or not after computing LU decomposition.
boolean	CholeskyDecomposer.isSPD()	Returns boolean indicating whether provided input matrix is Symmetric Positive Definite or not.
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.
double[]	SingularValueDecomposer.solve(double[] b)	Solves a linear system of equations of the following form: A * X = B using the pseudo-inverse to find the least squares solution.
double[]	SingularValueDecomposer.solve(double[] 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(double[] b, double[] 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(double[] b, double singularValueThreshold, double[] result)	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)	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.

Uses of NotAvailableException in com.irurueta.statistics

Methods in com.irurueta.statistics that throw NotAvailableException

Modifier and Type	Method	Description
void	MultivariateNormalDist.processCovariance()	Processes current covariance by decomposing it into a basis and its corresponding variances if needed.