Prototype

There is one prototype of gelss available, please see below.

gelss( MatrixA& a, MatrixB& b, VectorS& s, const Scalar >,
        int_t& rank );

Description

gelss (short for $FRIENDLY_NAME) provides a C++ interface to LAPACK routines SGELSS, DGELSS, CGELSS, and ZGELSS. gelss computes the minimum norm solution to a complex linear least squares problem:

Minimize 2-norm(| b - A*x |).

using the singular value decomposition (SVD) of A. A is an M-by-N matrix which may be rank-deficient.

Several right hand side vectors b and solution vectors x can be handled in a single call; they are stored as the columns of the M-by-NRHS right hand side matrix B and the N-by-NRHS solution matrix X.

The effective rank of A is determined by treating as zero those singular values which are less than RCOND times the largest singular value.

The selection of the LAPACK routine is done during compile-time, and is determined by the type of values contained in type MatrixA. The type of values is obtained through the value_type meta-function typename value_type<MatrixA>::type. The dispatching table below illustrates to which specific routine the code path will be generated.

Definition

Defined in header boost/numeric/bindings/lapack/driver/gelss.hpp.

Parameters or Requirements on Types

Complexity

Example

#include <boost/numeric/bindings/lapack/driver/gelss.hpp>
using namespace boost::numeric::bindings;

lapack::gelss( x, y, z );

this will output

[5] 0 1 2 3 4 5

Notes

See Also