test_lls
test_lls,
an Octave code which
implements linear least squares (LLS) test problems
which seek a vector x which minimizes the error in the
MxN 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.
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 MIT license
Languages:
test_lls is available in
a C version and
a C++ version and
a Fortran90 version and
a MATLAB version and
an Octave version and
a Python version.
Related Data and Programs:
test_lls_test
r8lib,
an Octave code which
contains many utility routines using double precision real (r8) arithmetic.
Reference:
-
Cleve Moler,
Numerical Computing with MATLAB,
SIAM, 2004,
ISBN13: 978-0-898716-60-3,
LC: QA297.M625,
ebook: https://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.
Last revised on 16 October 2022.