TEST_LLS
Linear Least Squares Test Problems
TEST_LLS,
a MATLAB 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=Axb, or, in cases where multiple minimizers exist,
to find the minimizer of minimal Euclidean norm.
TEST_LLS requires access to a compiled copy of the R8LIB library.
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 FORTRAN90 version and
a MATLAB version and
a Python version.
Related Data and Programs:
LLSQ,
a MATLAB library which
solves the simple linear least squares problem of finding the formula
of a straight line y=a*x+b which minimizes the rootmeansquare error
to a set of N data points.
R8LIB,
a MATLAB library which
contains many utility routines using double precision real (R8) arithmetic.
test_lls_test
Reference:

Cleve Moler,
Numerical Computing with MATLAB,
SIAM, 2004,
ISBN13: 9780898716603,
LC: QA297.M625,
ebook: http://www.mathworks.com/moler/chapters.html
Source Code:

p00_a.m
returns the matrix A for any least squares problem.

p00_b.m
returns the right hand side B for any least squares problem.

p00_m.m
returns the number of equations M for any least squares problem.

p00_n.m
returns the number of variables N for any least squares problem.

p00_prob_num.m
returns the number of least squares problems.

p00_x.m
returns the least squares solution X for any least squares problem.

p01_a.m
returns the matrix A for problem 1.

p01_b.m
returns the right hand side B for problem 1.

p01_m.m
returns the number of equations M for problem 1.

p01_n.m
returns the number of variables N for problem 1.

p01_x.m
returns the least squares solution X for problem 1.

p02_a.m
returns the matrix A for problem 2.

p02_b.m
returns the right hand side B for problem 2.

p02_m.m
returns the number of equations M for problem 2.

p02_n.m
returns the number of variables N for problem 2.

p02_x.m
returns the least squares solution X for problem 2.

p03_a.m
returns the matrix A for problem 3.

p03_b.m
returns the right hand side B for problem 3.

p03_m.m
returns the number of equations M for problem 3.

p03_n.m
returns the number of variables N for problem 3.

p03_x.m
returns the least squares solution X for problem 3.

p04_a.m
returns the matrix A for problem 4.

p04_b.m
returns the right hand side B for problem 4.

p04_m.m
returns the number of equations M for problem 4.

p04_n.m
returns the number of variables N for problem 4.

p04_x.m
returns the least squares solution X for problem 4.

p05_a.m
returns the matrix A for problem 5.

p05_b.m
returns the right hand side B for problem 5.

p05_m.m
returns the number of equations M for problem 5.

p05_n.m
returns the number of variables N for problem 5.

p05_x.m
returns the least squares solution X for problem 5.

p06_a.m
returns the matrix A for problem 6.

p06_b.m
returns the right hand side B for problem 6.

p06_m.m
returns the number of equations M for problem 6.

p06_n.m
returns the number of variables N for problem 6.

p06_x.m
returns the least squares solution X for problem 6.

timestamp.m
prints the YMDHMS date as a timestamp.
Last revised on 29 March 2019.