Uses of Class
com.irurueta.algebra.DecomposerException

Packages that use DecomposerException
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 DecomposerException in com.irurueta.algebra

    Subclasses of DecomposerException in com.irurueta.algebra
    Modifier and Type
    Class
    Description
    class 
    NoConvergenceException
    Exception thrown if some decomposer algorithm cannot converge
    Methods in com.irurueta.algebra that throw DecomposerException
    Modifier and Type
    Method
    Description
    static double
    Utils.cond(Matrix m)
    Computes condition number of provided matrix.
    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
    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'.
    static double
    Utils.det(Matrix m)
    Computes determinant of provided matrix.
    static Matrix
    Utils.inverse(double[] array)
    Computes array pseudo-inverse considering it as a column matrix.
    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 double
    Utils.norm2(double[] array)
    Computes two norm of provided input array.
    static double
    Utils.norm2(Matrix m)
    Computes two norm of provided input matrix.
    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 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.
    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.

  • Uses of DecomposerException in com.irurueta.statistics

    Methods in com.irurueta.statistics that throw DecomposerException
    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.mahalanobisDistance(double[] x)
    Computes the Mahalanobis distance of provided multivariate pot x for current mean and covariance values.
    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.
    double
    MultivariateNormalDist.squaredMahalanobisDistance(double[] x)
    Computes the squared Mahalanobis distance of provided multivariate pot x for current mean and covariance values.