**LA_GELSS** and **LA_GELSD** compute the minimum-norm least
squares solution to one or more real or complex linear systems
using the singular value decomposition of . Matrix
is rectangular and may be rank-deficient.
The vectors and corresponding solution vectors are
the columns of matrices denoted and , respectively.

The effective rank of is determined by treating as zero those
singular values which are less than times the largest singular
value. In addition to , the routines also return the right
singular vectors and, optionally, the rank and singular
values of .

**LA_GELSD** combines the singular value decomposition with
a divide and conquer technique. For large matrices it is often
much faster than **LA_GELSS** but uses more workspace.

Susan Blackford 2001-08-19