Linear Least Squares Test Problems

TEST_LLS is a Python library which implements linear least squares (LLS) test problems which seek a vector x which minimizes the error in the rectangular linear system A*x=b.

Some linear least squares problems include constraints on the data, such as requiring that every entry of X be positive. This library only contains unconstrained problems. For such problems, the task is typically to find a vector X which minimizes the Euclidean norm of the residual r=Ax-b, or, in cases where multiple minimizers exist, to find the minimizer of minimal Euclidean norm.


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


TEST_LLS is available in a C version and a C++ version and a FORTRAN77 version and a FORTRAN90 version and a MATLAB version and a Python version.

Related Data and Programs:


  1. Cleve Moler,
    Numerical Computing with MATLAB,
    SIAM, 2004,
    ISBN13: 978-0-898716-60-3,
    LC: QA297.M625,
    ebook: http://www.mathworks.com/moler/chapters.html

Source Code:

You can go up one level to the Python source codes.

Last revised on 25 August 2016.