NAG FL Interface
f08kqf (zgelsd)

Settings help

FL Name Style:

FL Specification Language:

1 Purpose

f08kqf computes the minimum norm solution to a complex linear least squares problem
minx b-Ax2 .  

2 Specification

Fortran Interface
Subroutine f08kqf ( m, n, nrhs, a, lda, b, ldb, s, rcond, rank, work, lwork, rwork, iwork, info)
Integer, Intent (In) :: m, n, nrhs, lda, ldb, lwork
Integer, Intent (Inout) :: iwork(*)
Integer, Intent (Out) :: rank, info
Real (Kind=nag_wp), Intent (In) :: rcond
Real (Kind=nag_wp), Intent (Inout) :: s(*), rwork(*)
Complex (Kind=nag_wp), Intent (Inout) :: a(lda,*), b(ldb,*)
Complex (Kind=nag_wp), Intent (Out) :: work(max(1,lwork))
C Header Interface
#include <nag.h>
void  f08kqf_ (const Integer *m, const Integer *n, const Integer *nrhs, Complex a[], const Integer *lda, Complex b[], const Integer *ldb, double s[], const double *rcond, Integer *rank, Complex work[], const Integer *lwork, double rwork[], Integer iwork[], Integer *info)
The routine may be called by the names f08kqf, nagf_lapackeig_zgelsd or its LAPACK name zgelsd.

3 Description

f08kqf uses the singular value decomposition (SVD) of A, where A is a complex m×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×r right-hand side matrix B and the n×r solution matrix X.
The problem is solved in three steps:
  1. 1.reduce the coefficient matrix A to bidiagonal form with Householder transformations, reducing the original problem into a ‘bidiagonal least squares problem’ (BLS);
  2. 2.solve the BLS using a divide-and-conquer approach;
  3. 3.apply back all the Householder transformations to solve the original least squares problem.
The effective rank of A is determined by treating as zero those singular values which are less than rcond times the largest singular value.

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

5 Arguments

1: m Integer Input
On entry: m, the number of rows of the matrix A.
Constraint: m0.
2: n Integer Input
On entry: n, the number of columns of the matrix A.
Constraint: n0.
3: nrhs Integer Input
On entry: r, the number of right-hand sides, i.e., the number of columns of the matrices B and X.
Constraint: nrhs0.
4: a(lda,*) Complex (Kind=nag_wp) array Input/Output
Note: the second dimension of the array a must be at least max(1,n).
On entry: the m×n coefficient matrix A.
On exit: the contents of a are destroyed.
5: lda Integer Input
On entry: the first dimension of the array a as declared in the (sub)program from which f08kqf is called.
Constraint: ldamax(1,m).
6: b(ldb,*) Complex (Kind=nag_wp) array Input/Output
Note: the second dimension of the array b must be at least max(1,nrhs).
On entry: the m×r right-hand side matrix B.
On exit: b is overwritten by the n×r solution matrix X. If mn and rank=n, the residual sum of squares for the solution in the ith column is given by the sum of squares of the modulus of elements n+1,,m in that column.
7: ldb Integer Input
On entry: the first dimension of the array b as declared in the (sub)program from which f08kqf is called.
Constraint: ldbmax(1,m,n).
8: s(*) Real (Kind=nag_wp) array Output
Note: the dimension of the array s must be at least max(1,min(m,n)) .
On exit: the singular values of A in decreasing order.
9: rcond Real (Kind=nag_wp) Input
On entry: used to determine the effective rank of A. Singular values s(i)rcond×s(1) are treated as zero. If rcond<0, machine precision is used instead.
10: rank Integer Output
On exit: the effective rank of A, i.e., the number of singular values which are greater than rcond×s(1).
11: work(max(1,lwork)) Complex (Kind=nag_wp) array Workspace
On exit: if info=0, the real part of work(1) contains the minimum value of lwork required for optimal performance.
12: lwork Integer Input
On entry: the dimension of the array work as declared in the (sub)program from which f08kqf is called.
The exact minimum amount of workspace needed depends on m, n and nrhs. As long as lwork is at least
max(1,m+n+r,2r+r×nrhs) ,  
where r=min(m,n), the code will execute correctly.
If lwork=−1, a workspace query is assumed; the routine only calculates the optimal size of the work array and the minimum size of the iwork array, and returns these values as the first entries of the work and iwork arrays, and no error message related to lwork is issued.
Suggested value: for optimal performance, lwork should generally be larger than the required minimum. Consider increasing lwork by at least nb×min(m,n) , where nb is the optimal block size.
Constraint: lworkmax(1,m+n+r,2r+r×nrhs) or lwork=−1.
13: rwork(*) Real (Kind=nag_wp) array Workspace
Note: the dimension of the array rwork must be at least max(1,lrwork), where lrwork is at least
10× n+2× n× smlsiz+8× n× nlvl+3× smlsiz× nrhs+(smlsiz+1)2 ,   if ​ mn  
10× m+2× m× smlsiz+8× m× nlvl+3× smlsiz× nrhs+(smlsiz+1)2 ,   if ​ m<n  
where smlsiz is equal to the maximum size of the subproblems at the bottom of the computation tree (usually about 25), and nlvl = max(0, int(log2(min(m,n)/(smlsiz+1))) +1 ) , the code will execute correctly.
On exit: if info=0, rwork(1) contains the required minimal size of lrwork.
14: iwork(*) Integer array Workspace
Note: the dimension of the array iwork must be at least max(1,liwork), where liwork is at least max(1,3×min(m,n)×nlvl+11×min(m,n)).
On exit: if info=0, iwork(1) returns the minimum liwork.
15: info Integer Output
On exit: info=0 unless the routine detects an error (see Section 6).

6 Error Indicators and Warnings

If info=-i, argument i had an illegal value. An explanatory message is output, and execution of the program is terminated.
The algorithm for computing the SVD failed to converge; value off-diagonal elements of an intermediate bidiagonal form did not converge to zero.

7 Accuracy

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

8 Parallelism and Performance

Background information to multithreading can be found in the Multithreading documentation.
f08kqf is threaded by NAG for parallel execution in multithreaded implementations of the NAG Library.
f08kqf 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 f08kcf.

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 -0.32-0.23i 0.35-0.60i 0.89+0.71i -0.19+0.06i -0.40+0.54i -0.05+0.20i -0.52-0.34i -0.45-0.45i 0.11-0.85i 0.60+0.01i -0.26-0.44i 0.87-0.11i -0.02-0.57i 1.44+0.80i 0.80-1.02i -0.43+0.17i -0.34-0.09i 1.14-0.78i 0.07+1.14i )  
b = ( 2.15-0.20i -2.24+1.82i 4.45-4.28i 5.70-6.25i ) .  
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 (f08kqfe.f90)

10.2 Program Data

Program Data (f08kqfe.d)

10.3 Program Results

Program Results (f08kqfe.r)