F08BNF (ZGELSY) (PDF version)
F08 Chapter Contents
F08 Chapter Introduction
NAG Library Manual

NAG Library Routine Document

F08BNF (ZGELSY)

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

F08BNF (ZGELSY) computes the minimum norm solution to a complex linear least squares problem
minx b-Ax2  
using a complete orthogonal factorization 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.

2  Specification

SUBROUTINE F08BNF ( M, N, NRHS, A, LDA, B, LDB, JPVT, RCOND, RANK, WORK, LWORK, RWORK, INFO)
INTEGER  M, N, NRHS, LDA, LDB, JPVT(*), RANK, LWORK, INFO
REAL (KIND=nag_wp)  RCOND, RWORK(*)
COMPLEX (KIND=nag_wp)  A(LDA,*), B(LDB,*), WORK(max(1,LWORK))
The routine may be called by its LAPACK name zgelsy.

3  Description

The right-hand side vectors are stored as the columns of the m by r matrix B and the solution vectors in the n by r matrix X.
F08BNF (ZGELSY) first computes a QR factorization with column pivoting
AP= Q R11 R12 0 R22 ,  
with R11 defined as the largest leading sub-matrix whose estimated condition number is less than 1/RCOND. The order of R11, RANK, is the effective rank of A.
Then, R22 is considered to be negligible, and R12 is annihilated by orthogonal transformations from the right, arriving at the complete orthogonal factorization
AP= Q T11 0 0 0 Z .  
The minimum norm solution is then
X = PZH T11-1 Q1H b 0  
where Q1 consists of the first RANK columns of Q.

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
Golub G H and Van Loan C F (1996) Matrix Computations (3rd Edition) Johns Hopkins University Press, Baltimore

5  Parameters

1:     M – INTEGERInput
On entry: m, the number of rows of the matrix A.
Constraint: M0.
2:     N – INTEGERInput
On entry: n, the number of columns of the matrix A.
Constraint: N0.
3:     NRHS – INTEGERInput
On entry: r, the number of right-hand sides, i.e., the number of columns of the matrices B and X.
Constraint: NRHS0.
4:     ALDA* – COMPLEX (KIND=nag_wp) arrayInput/Output
Note: the second dimension of the array A must be at least max1,N.
On entry: the m by n matrix A.
On exit: A has been overwritten by details of its complete orthogonal factorization.
5:     LDA – INTEGERInput
On entry: the first dimension of the array A as declared in the (sub)program from which F08BNF (ZGELSY) is called.
Constraint: LDAmax1,M.
6:     BLDB* – COMPLEX (KIND=nag_wp) arrayInput/Output
Note: the second dimension of the array B must be at least max1,NRHS.
On entry: the m by r right-hand side matrix B.
On exit: the n by r solution matrix X.
7:     LDB – INTEGERInput
On entry: the first dimension of the array B as declared in the (sub)program from which F08BNF (ZGELSY) is called.
Constraint: LDBmax1,M,N.
8:     JPVT* – INTEGER arrayInput/Output
Note: the dimension of the array JPVT must be at least max1,N.
On entry: if JPVTi0, the ith column of A is permuted to the front of AP, otherwise column i is a free column.
On exit: if JPVTi=k, then the ith column of AP was the kth column of A.
9:     RCOND – REAL (KIND=nag_wp)Input
On entry: used to determine the effective rank of A, which is defined as the order of the largest leading triangular sub-matrix R11 in the QR factorization of A, whose estimated condition number is <1/RCOND.
Suggested value: if the condition number of A is not known then RCOND=ε/2 (where ε is machine precision, see X02AJF) is a good choice. Negative values or values less than machine precision should be avoided since this will cause A to have an effective rank=minM,N that could be larger than its actual rank, leading to meaningless results.
10:   RANK – INTEGEROutput
On exit: the effective rank of A, i.e., the order of the sub-matrix R11. This is the same as the order of the sub-matrix T11 in the complete orthogonal factorization of A.
11:   WORKmax1,LWORK – COMPLEX (KIND=nag_wp) arrayWorkspace
On exit: if INFO=0, the real part of WORK1 contains the minimum value of LWORK required for optimal performance.
12:   LWORK – INTEGERInput
On entry: the dimension of the array WORK as declared in the (sub)program from which F08BNF (ZGELSY) 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,
LWORK max k + 2 × N + nb × N+1 , 2 × k + nb × NRHS ,  
where k = minM,N  and nb  is the optimal block size.
Constraint: LWORK k + max2×k,N+1,k+NRHS , where ​ k = minM,N  or
LWORK=-1.
13:   RWORK* – REAL (KIND=nag_wp) arrayWorkspace
Note: the dimension of the array RWORK must be at least max1,2×N.
14:   INFO – INTEGEROutput
On exit: INFO=0 unless the routine detects an error (see Section 6).

6  Error Indicators and Warnings

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

See Section 4.5 of Anderson et al. (1999) for details of error bounds.

8  Parallelism and Performance

F08BNF (ZGELSY) is threaded by NAG for parallel execution in multithreaded implementations of the NAG Library.
F08BNF (ZGELSY) makes calls to BLAS and/or LAPACK routines, which may be threaded within the vendor library used by this implementation. Consult the documentation for the vendor library for further information.
Please consult the X06 Chapter Introduction for information on how to control and interrogate the OpenMP environment used within this routine. Please also consult the Users' Note for your implementation for any additional implementation-specific information.

9  Further Comments

The real analogue of this routine is F08BAF (DGELSY).

10  Example

This example solves the linear least squares problem
minx b-Ax2  
for the solution, x, of minimum norm, where
A = 0.47-0.34i -0.40+0.54i 0.60+0.01i 0.80-1.02i -0.32-0.23i -0.05+0.20i -0.26-0.44i -0.43+0.17i 0.35-0.60i -0.52-0.34i 0.87-0.11i -0.34-0.09i 0.89+0.71i -0.45-0.45i -0.02-0.57i 1.14-0.78i -0.19+0.06i 0.11-0.85i 1.44+0.80i 0.07+1.14i  
and
b = -1.08-2.59i -2.61-1.49i 3.13-3.61i 7.33-8.01i 9.12+7.63i .  
A tolerance of 0.01 is used to determine the effective rank of A.
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.

10.1  Program Text

Program Text (f08bnfe.f90)

10.2  Program Data

Program Data (f08bnfe.d)

10.3  Program Results

Program Results (f08bnfe.r)


F08BNF (ZGELSY) (PDF version)
F08 Chapter Contents
F08 Chapter Introduction
NAG Library Manual

© The Numerical Algorithms Group Ltd, Oxford, UK. 2015