Uses of Class
com.irurueta.algebra.NotReadyException

Packages that use NotReadyException

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 NotReadyException in com.irurueta.algebra

Methods in com.irurueta.algebra that throw NotReadyException

Modifier and Type	Method	Description
void	CholeskyDecomposer.decompose()	This method computes Cholesky matrix decomposition, which consists on factoring provided input matrix whenever it is square, symmetric and positive definite into a lower triangulator factor such that it follows next expression: A = L * L' where A is input matrix and L is lower triangular factor (L' is its transposed).
abstract void	Decomposer.decompose()	This method computes matrix decomposition for each decomposer type.
void	EconomyQRDecomposer.decompose()	This method computes QR matrix decomposition, which consists on factoring provided input matrix into an orthogonal matrix (Q) and an upper triangular matrix (R).
void	LUDecomposer.decompose()	This method computes LU matrix decomposition, which consists on retrieving two triangular matrices (Lower triangular and Upper triangular) as a decomposition of provided input matrix.
void	QRDecomposer.decompose()	This method computes LU matrix decomposition, which consists on retrieving two triangular matrices (Lower triangular and Upper triangular) as a decomposition of provided input matrix.
void	RQDecomposer.decompose()	This method computes RQ matrix decomposition, which consists on factoring provided input matrix into an upper triangular matrix (R) and an orthogonal matrix (Q).
void	SingularValueDecomposer.decompose()	This method computes Singular Value matrix decomposition, which consists on factoring provided input matrix into three factors consisting of 2 unary matrices and 1 diagonal matrix containing singular values, following next expression: A = U * S * V'.

Uses of NotReadyException in com.irurueta.statistics

Methods in com.irurueta.statistics that throw NotReadyException

Modifier and Type	Method	Description
double	MultivariateNormalDist.cdf(double[] x)	Evaluates the cumulative distribution function (c.d.f.) of a Gaussian distribution having current mean and covariance values.
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.
double[]	MultivariateNormalDist.invcdf(double p)	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)	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)	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 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)	Evaluates the inverse cumulative distribution function of a multivariate Gaussian distribution for current mean and covariance values and provided probability value.
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.
double	MultivariateNormalDist.p(double[] x)	Evaluates the probability density function (p.d.f.) of a multivariate Gaussian distribution having current mean and covariance at point x.
void	MultivariateNormalDist.processCovariance()	Processes current covariance by decomposing it into a basis and its corresponding variances if needed.