TEST_LLS
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.

Licensing:

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

Languages:

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:

Reference:

  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.