F08ZEF (DGGQRF) (PDF version)
F08 Chapter Contents
F08 Chapter Introduction
NAG Library Manual

NAG Library Routine Document

F08ZEF (DGGQRF)

Note:  before using this routine, please read the Users' Note for your implementation to check the interpretation of bold italicised terms and other implementation-dependent details.

+ Contents

    1  Purpose
    7  Accuracy

1  Purpose

F08ZEF (DGGQRF) computes a generalized QR factorization of a real matrix pair A,B, where A is an n by m matrix and B is an n by p matrix.

2  Specification

SUBROUTINE F08ZEF ( N, M, P, A, LDA, TAUA, B, LDB, TAUB, WORK, LWORK, INFO)
INTEGER  N, M, P, LDA, LDB, LWORK, INFO
REAL (KIND=nag_wp)  A(LDA,*), TAUA(min(N,M)), B(LDB,*), TAUB(min(N,P)), WORK(max(1,LWORK))
The routine may be called by its LAPACK name dggqrf.

3  Description

F08ZEF (DGGQRF) forms the generalized QR factorization of an n by m matrix A and an n by p matrix B 
A =QR ,   B=QTZ ,
where Q is an n by n orthogonal matrix, Z is a p by p orthogonal matrix and R and T are of the form
R = mm(R11) n-m 0 ,   if ​nm; nm-nn(R11R12) ,   if ​n<m,
with R11 upper triangular,
T = p-nnn(0T12) ,   if ​np, pn-p(T11) p T21 ,   if ​n>p,
with T12 or T21 upper triangular.
In particular, if B is square and nonsingular, the generalized QR factorization of A and B implicitly gives the QR factorization of B-1A as
B-1A= ZT T-1 R .

4  References

Anderson E, Bai Z, Bischof C, Blackford S, Demmel J, Dongarra J J, Du Croz J J, Greenbaum A, Hammarling S, McKenney A and Sorensen D (1999) LAPACK Users' Guide (3rd Edition) SIAM, Philadelphia http://www.netlib.org/lapack/lug
Anderson E, Bai Z and Dongarra J (1992) Generalized QR factorization and its applications Linear Algebra Appl. (Volume 162–164) 243–271
Hammarling S (1987) The numerical solution of the general Gauss-Markov linear model Mathematics in Signal Processing (eds T S Durrani, J B Abbiss, J E Hudson, R N Madan, J G McWhirter and T A Moore) 441–456 Oxford University Press
Paige C C (1990) Some aspects of generalized QR factorizations . In Reliable Numerical Computation (eds M G Cox and S Hammarling) 73–91 Oxford University Press

5  Parameters

1:     N – INTEGERInput
On entry: n, the number of rows of the matrices A and B.
Constraint: N0.
2:     M – INTEGERInput
On entry: m, the number of columns of the matrix A.
Constraint: M0.
3:     P – INTEGERInput
On entry: p, the number of columns of the matrix B.
Constraint: P0.
4:     A(LDA,*) – REAL (KIND=nag_wp) arrayInput/Output
Note: the second dimension of the array A must be at least max1,M.
On entry: the n by m matrix A.
On exit: the elements on and above the diagonal of the array contain the minn,m by m upper trapezoidal matrix R (R is upper triangular if nm); the elements below the diagonal, with the array TAUA, represent the orthogonal matrix Q as a product of minn,m elementary reflectors (see Section 3.3.6 in the F08 Chapter Introduction).
5:     LDA – INTEGERInput
On entry: the first dimension of the array A as declared in the (sub)program from which F08ZEF (DGGQRF) is called.
Constraint: LDAmax1,N.
6:     TAUA(minN,M) – REAL (KIND=nag_wp) arrayOutput
On exit: the scalar factors of the elementary reflectors which represent the orthogonal matrix Q.
7:     B(LDB,*) – REAL (KIND=nag_wp) arrayInput/Output
Note: the second dimension of the array B must be at least max1,P.
On entry: the n by p matrix B.
On exit: if np, the upper triangle of the subarray B 1:n , p-n+1:p  contains the n by n upper triangular matrix T12.
If n>p, the elements on and above the n-pth subdiagonal contain the n by p upper trapezoidal matrix T; the remaining elements, with the array TAUB, represent the orthogonal matrix Z as a product of elementary reflectors (see Section 3.3.6 in the F08 Chapter Introduction).
8:     LDB – INTEGERInput
On entry: the first dimension of the array B as declared in the (sub)program from which F08ZEF (DGGQRF) is called.
Constraint: LDBmax1,N.
9:     TAUB(minN,P) – REAL (KIND=nag_wp) arrayOutput
On exit: the scalar factors of the elementary reflectors which represent the orthogonal matrix Z.
10:   WORK(max1,LWORK) – REAL (KIND=nag_wp) arrayWorkspace
On exit: if INFO=0, WORK1 contains the minimum value of LWORK required for optimal performance.
11:   LWORK – INTEGERInput
On entry: the dimension of the array WORK as declared in the (sub)program from which F08ZEF (DGGQRF) is called.
If LWORK=-1, a workspace query is assumed; the routine only calculates the optimal size of the WORK array, returns this value as the first entry of the WORK array, and no error message related to LWORK is issued.
Suggested value: for optimal performance, LWORKmaxN,M,P×maxnb1,nb2,nb3, where nb1 is the optimal block size for the QR factorization of an n by m matrix, nb2 is the optimal block size for the RQ factorization of an n by p matrix, and nb3 is the optimal block size for a call of F08AGF (DORMQR).
Constraint: LWORKmax1,N,M,P or LWORK=-1.
12:   INFO – INTEGEROutput
On exit: INFO=0 unless the routine detects an error (see Section 6).

6  Error Indicators and Warnings

Errors or warnings detected by the routine:
INFO<0
If INFO=-i, argument i had an illegal value. An explanatory message is output, and execution of the program is terminated.

7  Accuracy

The computed generalized QR factorization is the exact factorization for nearby matrices A+E and B+F, where
E2 = Oε A2   and   F2= Oε B2 ,
and ε is the machine precision.

8  Further Comments

The orthogonal matrices Q and Z may be formed explicitly by calls to F08AFF (DORGQR) and F08CJF (DORGRQ) respectively. F08AGF (DORMQR) may be used to multiply Q by another matrix and F08CKF (DORMRQ) may be used to multiply Z by another matrix.
The complex analogue of this routine is F08ZSF (ZGGQRF).

9  Example

This example solves the general Gauss–Markov linear model problem
minx y2   subject to   d=Ax+By
where
A = -0.57 -1.28 -0.39 -1.93 1.08 -0.31 2.30 0.24 -0.40 -0.02 1.03 -1.43 ,   B= 0.5 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 2.0 0.0 0.0 0.0 0.0 5.0   and   d= 1.32 -4.00 5.52 3.24 .
The solution is obtained by first computing a generalized QR factorization of the matrix pair A,B. The example illustrates the general solution process, although the above data corresponds to a simple weighted least squares problem.
Note that the block size (NB) of 64 assumed in this example is not realistic for such a small problem, but should be suitable for large problems.

9.1  Program Text

Program Text (f08zefe.f90)

9.2  Program Data

Program Data (f08zefe.d)

9.3  Program Results

Program Results (f08zefe.r)


F08ZEF (DGGQRF) (PDF version)
F08 Chapter Contents
F08 Chapter Introduction
NAG Library Manual

© The Numerical Algorithms Group Ltd, Oxford, UK. 2012