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    In This Topic

    This module contains the following utilities functions, to help manipulating matrix and modeling.

    List of functions

    CHOLESKY Returns the lower cholesky factor of a symmetric, positive definite matrix
    CORR.2.COV Converts a correlation matrix to a covariance matrix
    CORR.MAT Returns the correlation matrix.
    COV.2.CORR Converts a covariance matrix to a correlation matrix
    DIAG Returns a square diagonal matrix with the elements of the argument on the main diagonal.
    EIGEN.VALUES Returns the eigenvalues of a symmetric matrix
    EIGEN.VECTORS Returns the eigenvectors of a symmetric matrix
    EXTRACT.DIAG Returns the main diagonal of a square matrix
    IS.PSD Check if the matrix is positive semi-definite
    NEAREST.CORR Find the nearest correlation matrix that is positive semi-definite.
    NEAREST.COV Find the nearest covariance matrix that is positive semi-definite, and leaves the variance unchanged.
    ROUND.SMALL Round small values (abs(value)<1e6) in a matrix to zero
    SINGULAR.VALUES Returns the singular values of a matrix (SVD)
    TRACE Returns the sum of the diagonal coefficients of a matrix
    UNVEC Form a matrix from a vector (inverse of the function VEC)
    UNVECH Form a symmetric matrix (d x d) from a vector of length d(d+1)/2 (inverse of the function VECH).
    VARCOV.MAT Returns the variance covariance matrix.
    VEC Takes a square matrix and stacks the columns into a single vector
    VECH Takes a symmetric d x d matrix and stacks the upper triangular half into a single vector of length d(d+1)/2.