There is one prototype of ggglm
available, please see below.
ggglm( MatrixA& a, MatrixB& b, VectorD& d, VectorX& x, VectorY& y );
ggglm (short for $FRIENDLY_NAME)
provides a C++ interface to LAPACK routines SGGGLM, DGGGLM, CGGGLM, and
ZGGGLM. ggglm solves
a general Gauss-Markov linear model (GLM) problem:
minimize || y ||_2 subject to d = A*x + B*y x
where A is an N-by-M matrix, B is an N-by-P matrix, and d is a given N-vector. It is assumed that M <= N <= M+P, and
rank(A) = M and rank( A B ) = N.
Under these assumptions, the constrained equation is always consistent, and there is a unique solution x and a minimal 2-norm solution y, which is obtained using a generalized QR factorization of the matrices (A, B) given by
A = Q*(R), B = Q*T*Z. (0)
In particular, if matrix B is square nonsingular, then the problem GLM is equivalent to the following weighted linear least squares problem
minimize || inv(B)*(d-A*x) ||_2 x
where inv(B) denotes the inverse of B.
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.
Table 1.124. Dispatching of ggglm
|
Value type of MatrixA |
LAPACK routine |
|---|---|
|
|
SGGGLM |
|
|
DGGGLM |
|
|
CGGGLM |
|
|
ZGGGLM |
Defined in header boost/numeric/bindings/lapack/driver/ggglm.hpp.
Parameters
The definition of term 1
The definition of term 2
The definition of term 3.
Definitions may contain paragraphs.
#include <boost/numeric/bindings/lapack/driver/ggglm.hpp> using namespace boost::numeric::bindings; lapack::ggglm( x, y, z );
this will output
[5] 0 1 2 3 4 5