asa007, a Python code which computes the inverse of a symmetric positive definite (SPD) matrix, by Michael Healy.

This is a version of Applied Statistics Algorithm 7.

The algorithm implemented here uses a compressed storage for both the matrix A and the factor U. This saves some storage, but can make computations a little awkward.


The computer code and data files described and made available on this web page are distributed under the MIT license


asa007 is available in a C version and a C++ version and a Fortran90 version and a MATLAB version and a Python version.

Related Data and Programs:

asa006, a Python code which computes the Cholesky factorization of a symmetric positive definite (SPD) matrix.

asa047, a Python code which implements the Nelder-Mead minimization algorithm.


Michael Healy


  1. Michael Healy,
    Algorithm AS 7: Inversion of a Positive Semi-Definite Symmetric Matrix,
    Applied Statistics,
    Volume 17, Number 2, 1968, pages 198-199.

Source Code:

Last revised on 12 August 2022.