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Factorize

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Demo
Demo
 
 
Doc
Doc
 
 
Test
Test
 
 
private
private
 
 
Contents.m
Contents.m
 
 
README.txt
README.txt
 
 
cod.m
cod.m
 
 
cod_qmult.m
cod_qmult.m
 
 
cod_sparse.m
cod_sparse.m
 
 
factorization.m
factorization.m
 
 
factorization_chol_dense.m
factorization_chol_dense.m
 
 
factorization_chol_sparse.m
factorization_chol_sparse.m
 
 
factorization_cod_dense.m
factorization_cod_dense.m
 
 
factorization_cod_sparse.m
factorization_cod_sparse.m
 
 
factorization_ldl_dense.m
factorization_ldl_dense.m
 
 
factorization_ldl_sparse.m
factorization_ldl_sparse.m
 
 
factorization_lu_dense.m
factorization_lu_dense.m
 
 
factorization_lu_sparse.m
factorization_lu_sparse.m
 
 
factorization_qr_dense.m
factorization_qr_dense.m
 
 
factorization_qr_sparse.m
factorization_qr_sparse.m
 
 
factorization_qrt_dense.m
factorization_qrt_dense.m
 
 
factorization_qrt_sparse.m
factorization_qrt_sparse.m
 
 
factorization_svd.m
factorization_svd.m
 
 
factorize.m
factorize.m
 
 
inverse.m
inverse.m
 
 
rq.m
rq.m
 
 

README.txt

FACTORIZE:  an object-oriented method for solving linear systems and least
squares problems.

See the Factorize/Contents.m file for more details on how to install and test
this package.  For a demo, see Factorize/Demo (run "fdemo" from the MATLAB
Command window).  For additional documentation, see Factorize/Doc.

The COD function for sparse matrices requires the SPQR mexFunction from the
SuiteSparse library.  The simplest way to get this is to install all of
SuiteSparse from http://www.suitesparse.com.  The FACTORIZE method can be used
without SPQR; in this case, the COD for sparse matrices is not used.  This has
no effect on the use of this method for full-rank matrices, since COD is used
only for rank-deficient matrices.

Copyright 2011-2012, Timothy A. Davis, http://www.suitesparse.com