NAG FL Interface
f04fff (real_​toeplitz_​solve)

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1 Purpose

f04fff solves the equations Tx=b, where T is a real symmetric positive definite Toeplitz matrix.

2 Specification

Fortran Interface
Subroutine f04fff ( n, t, b, x, wantp, p, work, ifail)
Integer, Intent (In) :: n
Integer, Intent (Inout) :: ifail
Real (Kind=nag_wp), Intent (In) :: t(0:*), b(*)
Real (Kind=nag_wp), Intent (Inout) :: p(*)
Real (Kind=nag_wp), Intent (Out) :: x(n), work(2*(n-1))
Logical, Intent (In) :: wantp
C Header Interface
#include <nag.h>
void  f04fff_ (const Integer *n, const double t[], const double b[], double x[], const logical *wantp, double p[], double work[], Integer *ifail)
The routine may be called by the names f04fff or nagf_linsys_real_toeplitz_solve.

3 Description

f04fff solves the equations
Tx=b,  
where T is the n×n symmetric positive definite Toeplitz matrix
T=( τ0 τ1 τ2 τn-1 τ1 τ0 τ1 τn-2 τ2 τ1 τ0 τn-3 . . . . τn-1 τn-2 τn-3 τ0 )  
and b is an n-element vector.
The routine uses the method of Levinson (see Levinson (1947) and Golub and Van Loan (1996)). Optionally, the reflection coefficients for each step may also be returned.

4 References

Bunch J R (1985) Stability of methods for solving Toeplitz systems of equations SIAM J. Sci. Statist. Comput. 6 349–364
Bunch J R (1987) The weak and strong stability of algorithms in numerical linear algebra Linear Algebra Appl. 88/89 49–66
Cybenko G (1980) The numerical stability of the Levinson–Durbin algorithm for Toeplitz systems of equations SIAM J. Sci. Statist. Comput. 1 303–319
Golub G H and Van Loan C F (1996) Matrix Computations (3rd Edition) Johns Hopkins University Press, Baltimore
Levinson N (1947) The Weiner RMS error criterion in filter design and prediction J. Math. Phys. 25 261–278

5 Arguments

1: n Integer Input
On entry: the order of the Toeplitz matrix T.
Constraint: n0. When n=0, an immediate return is effected.
2: t(0:*) Real (Kind=nag_wp) array Input
Note: the dimension of the array t must be at least max(1,n).
On entry: t(i) must contain the value τi, for i=0,1,,n-1.
Constraint: t(0)>0.0. Note that if this is not true, the Toeplitz matrix cannot be positive definite.
3: b(*) Real (Kind=nag_wp) array Input
Note: the dimension of the array b must be at least max(1,n).
On entry: the right-hand side vector b.
4: x(n) Real (Kind=nag_wp) array Output
On exit: the solution vector x.
5: wantp Logical Input
On entry: must be set to .TRUE. if the reflection coefficients are required, and must be set to .FALSE. otherwise.
6: p(*) Real (Kind=nag_wp) array Output
Note: the dimension of the array p must be at least max(1,n-1) if wantp=.TRUE., and at least 1 otherwise.
On exit: with wantp as .TRUE., the ith element of p contains the reflection coefficient, pi, for the ith step, for i=1,2,,n-1. (See Section 9.) If wantp is .FALSE., p is not referenced.
7: work(2×(n-1)) Real (Kind=nag_wp) array Workspace
8: ifail Integer Input/Output
On entry: ifail must be set to 0, −1 or 1 to set behaviour on detection of an error; these values have no effect when no error is detected.
A value of 0 causes the printing of an error message and program execution will be halted; otherwise program execution continues. A value of −1 means that an error message is printed while a value of 1 means that it is not.
If halting is not appropriate, the value −1 or 1 is recommended. If message printing is undesirable, then the value 1 is recommended. Otherwise, the value −1 is recommended since useful values can be provided in some output arguments even when ifail0 on exit. When the value -1 or 1 is used it is essential to test the value of ifail on exit.
On exit: ifail=0 unless the routine detects an error or a warning has been flagged (see Section 6).

6 Error Indicators and Warnings

If on entry ifail=0 or −1, explanatory error messages are output on the current error message unit (as defined by x04aaf).
Errors or warnings detected by the routine:
Note: in some cases f04fff may return useful information.
ifail>0
Principal minor value is not positive definite. Value of the reflection coefficient is value.
The first (ifail-1) elements of x return the solution of the equations
Tifail-1x=(b1,b2,,bifail-1)T,  
where Tk is the kth principal minor of T.
ifail=-1
On entry, n=value.
Constraint: n0.
On entry, t(0)=value.
Constraint: t(0)>0.0.
ifail=-99
An unexpected error has been triggered by this routine. Please contact NAG.
See Section 7 in the Introduction to the NAG Library FL Interface for further information.
ifail=-399
Your licence key may have expired or may not have been installed correctly.
See Section 8 in the Introduction to the NAG Library FL Interface for further information.
ifail=-999
Dynamic memory allocation failed.
See Section 9 in the Introduction to the NAG Library FL Interface for further information.

7 Accuracy

The computed solution of the equations certainly satisfies
r = Tx-b ,  
where r is approximately bounded by
r cεC(T) ,  
c being a modest function of n, ε being the machine precision and C(T) being the condition number of T with respect to inversion. This bound is almost certainly pessimistic, but it seems unlikely that the method of Levinson is backward stable, so caution should be exercised when T is ill-conditioned. The following bound on T-1 holds:
max( 1 i=1 n-1 (1-pi2) , 1 i=1 n-1 (1-pi) ) T-11 i=1 n-1 ( 1+|pi| 1-|pi| ) .  
(See Golub and Van Loan (1996).) The norm of T-1 may also be estimated using routine f04ydf. For further information on stability issues see Bunch (1985), Bunch (1987), Cybenko (1980) and Golub and Van Loan (1996).

8 Parallelism and Performance

Background information to multithreading can be found in the Multithreading documentation.
f04fff 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 number of floating-point operations used by f04fff is approximately 4n2.
If yi is the solution of the equations
Tiyi=-(τ1τ2τi)T,  
then the partial correlation coefficient pi is defined as the ith element of yi.

10 Example

This example finds the solution of the equations Tx=b, where
T=( 4 3 2 1 3 4 3 2 2 3 4 3 1 2 3 4 )   and  b=( 1 1 1 1 ) .  

10.1 Program Text

Program Text (f04fffe.f90)

10.2 Program Data

Program Data (f04fffe.d)

10.3 Program Results

Program Results (f04fffe.r)