F08 Chapter Contents
F08 Chapter Introduction
NAG Library Manual

# NAG Library Routine DocumentF08BEF (DGEQPF)

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.

## 1  Purpose

F08BEF (DGEQPF) computes the $QR$ factorization, with column pivoting, of a real $m$ by $n$ matrix.

## 2  Specification

 SUBROUTINE F08BEF ( M, N, A, LDA, JPVT, TAU, WORK, INFO)
 INTEGER M, N, LDA, JPVT(*), INFO REAL (KIND=nag_wp) A(LDA,*), TAU(min(M,N)), WORK(3*N)
The routine may be called by its LAPACK name dgeqpf.

## 3  Description

F08BEF (DGEQPF) forms the $QR$ factorization, with column pivoting, of an arbitrary rectangular real $m$ by $n$ matrix.
If $m\ge n$, the factorization is given by:
 $AP= Q R 0 ,$
where $R$ is an $n$ by $n$ upper triangular matrix, $Q$ is an $m$ by $m$ orthogonal matrix and $P$ is an $n$ by $n$ permutation matrix. It is sometimes more convenient to write the factorization as
 $AP= Q1 Q2 R 0 ,$
which reduces to
 $AP= Q1 R ,$
where ${Q}_{1}$ consists of the first $n$ columns of $Q$, and ${Q}_{2}$ the remaining $m-n$ columns.
If $m, $R$ is trapezoidal, and the factorization can be written
 $AP= Q R1 R2 ,$
where ${R}_{1}$ is upper triangular and ${R}_{2}$ is rectangular.
The matrix $Q$ is not formed explicitly but is represented as a product of $\mathrm{min}\phantom{\rule{0.125em}{0ex}}\left(m,n\right)$ elementary reflectors (see the F08 Chapter Introduction for details). Routines are provided to work with $Q$ in this representation (see Section 9).
Note also that for any $k, the information returned in the first $k$ columns of the array A represents a $QR$ factorization of the first $k$ columns of the permuted matrix $AP$.
The routine allows specified columns of $A$ to be moved to the leading columns of $AP$ at the start of the factorization and fixed there. The remaining columns are free to be interchanged so that at the $i$th stage the pivot column is chosen to be the column which maximizes the $2$-norm of elements $i$ to $m$ over columns $i$ to $n$.

## 4  References

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

## 5  Parameters

1:     $\mathrm{M}$ – INTEGERInput
On entry: $m$, the number of rows of the matrix $A$.
Constraint: ${\mathbf{M}}\ge 0$.
2:     $\mathrm{N}$ – INTEGERInput
On entry: $n$, the number of columns of the matrix $A$.
Constraint: ${\mathbf{N}}\ge 0$.
3:     $\mathrm{A}\left({\mathbf{LDA}},*\right)$ – REAL (KIND=nag_wp) arrayInput/Output
Note: the second dimension of the array A must be at least $\mathrm{max}\phantom{\rule{0.125em}{0ex}}\left(1,{\mathbf{N}}\right)$.
On entry: the $m$ by $n$ matrix $A$.
On exit: if $m\ge n$, the elements below the diagonal are overwritten by details of the orthogonal matrix $Q$ and the upper triangle is overwritten by the corresponding elements of the $n$ by $n$ upper triangular matrix $R$.
If $m, the strictly lower triangular part is overwritten by details of the orthogonal matrix $Q$ and the remaining elements are overwritten by the corresponding elements of the $m$ by $n$ upper trapezoidal matrix $R$.
4:     $\mathrm{LDA}$ – INTEGERInput
On entry: the first dimension of the array A as declared in the (sub)program from which F08BEF (DGEQPF) is called.
Constraint: ${\mathbf{LDA}}\ge \mathrm{max}\phantom{\rule{0.125em}{0ex}}\left(1,{\mathbf{M}}\right)$.
5:     $\mathrm{JPVT}\left(*\right)$ – INTEGER arrayInput/Output
Note: the dimension of the array JPVT must be at least $\mathrm{max}\phantom{\rule{0.125em}{0ex}}\left(1,{\mathbf{N}}\right)$.
On entry: if ${\mathbf{JPVT}}\left(i\right)\ne 0$, then the $i$ th column of $A$ is moved to the beginning of $AP$ before the decomposition is computed and is fixed in place during the computation. Otherwise, the $i$ th column of $A$ is a free column (i.e., one which may be interchanged during the computation with any other free column).
On exit: details of the permutation matrix $P$. More precisely, if ${\mathbf{JPVT}}\left(i\right)=k$, then the $k$th column of $A$ is moved to become the $i$ th column of $AP$; in other words, the columns of $AP$ are the columns of $A$ in the order ${\mathbf{JPVT}}\left(1\right),{\mathbf{JPVT}}\left(2\right),\dots ,{\mathbf{JPVT}}\left(n\right)$.
6:     $\mathrm{TAU}\left(\mathrm{min}\phantom{\rule{0.125em}{0ex}}\left({\mathbf{M}},{\mathbf{N}}\right)\right)$ – REAL (KIND=nag_wp) arrayOutput
On exit: further details of the orthogonal matrix $Q$.
7:     $\mathrm{WORK}\left(3×{\mathbf{N}}\right)$ – REAL (KIND=nag_wp) arrayWorkspace
8:     $\mathrm{INFO}$ – INTEGEROutput
On exit: ${\mathbf{INFO}}=0$ unless the routine detects an error (see Section 6).

## 6  Error Indicators and Warnings

${\mathbf{INFO}}<0$
If ${\mathbf{INFO}}=-i$, argument $i$ had an illegal value. An explanatory message is output, and execution of the program is terminated.

## 7  Accuracy

The computed factorization is the exact factorization of a nearby matrix $\left(A+E\right)$, where
 $E2 = Oε A2 ,$
and $\epsilon$ is the machine precision.

## 8  Parallelism and Performance

F08BEF (DGEQPF) is not threaded by NAG in any implementation.
F08BEF (DGEQPF) 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.

The total number of floating-point operations is approximately $\frac{2}{3}{n}^{2}\left(3m-n\right)$ if $m\ge n$ or $\frac{2}{3}{m}^{2}\left(3n-m\right)$ if $m.
To form the orthogonal matrix $Q$ F08BEF (DGEQPF) may be followed by a call to F08AFF (DORGQR):
```CALL DORGQR(M,M,MIN(M,N),A,LDA,TAU,WORK,LWORK,INFO)
```
but note that the second dimension of the array A must be at least M, which may be larger than was required by F08BEF (DGEQPF).
When $m\ge n$, it is often only the first $n$ columns of $Q$ that are required, and they may be formed by the call:
```CALL DORGQR(M,N,N,A,LDA,TAU,WORK,LWORK,INFO)
```
To apply $Q$ to an arbitrary real rectangular matrix $C$, F08BEF (DGEQPF) may be followed by a call to F08AGF (DORMQR). For example,
```CALL DORMQR('Left','Transpose',M,P,MIN(M,N),A,LDA,TAU,C,LDC,WORK, &
LWORK,INFO)```
forms $C={Q}^{\mathrm{T}}C$, where $C$ is $m$ by $p$.
To compute a $QR$ factorization without column pivoting, use F08AEF (DGEQRF).
The complex analogue of this routine is F08BSF (ZGEQPF).

## 10  Example

This example finds the basic solutions for the linear least squares problems
 $minimize⁡ Axi - bi 2 , i=1,2$
where ${b}_{1}$ and ${b}_{2}$ are the columns of the matrix $B$,
 $A = -0.09 0.14 -0.46 0.68 1.29 -1.56 0.20 0.29 1.09 0.51 -1.48 -0.43 0.89 -0.71 -0.96 -1.09 0.84 0.77 2.11 -1.27 0.08 0.55 -1.13 0.14 1.74 -1.59 -0.72 1.06 1.24 0.34 and B= -0.01 -0.04 0.04 -0.03 0.05 0.01 -0.03 -0.02 0.02 0.05 -0.06 0.07 .$
Here $A$ is approximately rank-deficient, and hence it is preferable to use F08BEF (DGEQPF) rather than F08AEF (DGEQRF).

### 10.1  Program Text

Program Text (f08befe.f90)

### 10.2  Program Data

Program Data (f08befe.d)

### 10.3  Program Results

Program Results (f08befe.r)