A Matlab Toolbox for

Sparse Least Squares problems

This toolbox in MatLab is a set of rutines for solving sparse least square problem;

min ||Ax-b||₂

the constrained least squares problem with non negativity constraints;

min ||Ax-b||₂ s.t. 0 < x

and problems with box constraints,

min ||Ax-b||₂ s.t. l < x < u

Click on a name to get more information

sqr	Sparse multifrontal QR factorisation.
sqr2	Sparse multifrontal QR factorisation.

csne	Solve sparse linear least squares problem by the corrected semi normal equations. R'Rx=A'b with one step of itertive refinement.
qls	Solve sparse linear least squares problem by QR factorization.
sbls	Solve linear least squares with box constraints by an interior point method.
sbls2	Solve linear least squares with box constraints by an active set method.
snnls	Solve sparse linear least squarest problem with nonnegativity constraints by an active set method.

sblsgen	Generate random sparse least square test problems with box constraints.
quadres	Calculate a residual using quadruple precision. Must be compiled with a C compiler.

For more information, please email to: Mikael Adlers, Åke Björck or Pontus Matstoms