C05RBF (PDF version)
C05 Chapter Contents
C05 Chapter Introduction
NAG Library Manual

NAG Library Routine Document

C05RBF

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

C05RBF is an easy-to-use routine that finds a solution of a system of nonlinear equations by a modification of the Powell hybrid method. You must provide the Jacobian.

2  Specification

SUBROUTINE C05RBF ( FCN, N, X, FVEC, FJAC, XTOL, IUSER, RUSER, IFAIL)
INTEGER  N, IUSER(*), IFAIL
REAL (KIND=nag_wp)  X(N), FVEC(N), FJAC(N,N), XTOL, RUSER(*)
EXTERNAL  FCN

3  Description

The system of equations is defined as:
fi x1,x2,,xn = 0 ,   i= 1, 2, , n .
C05RBF is based on the MINPACK routine HYBRJ1 (see Moré et al. (1980)). It chooses the correction at each step as a convex combination of the Newton and scaled gradient directions. The Jacobian is updated by the rank-1 method of Broyden. At the starting point, the Jacobian is requested, but it is not asked for again until the rank-1 method fails to produce satisfactory progress. For more details see Powell (1970).

4  References

Moré J J, Garbow B S and Hillstrom K E (1980) User guide for MINPACK-1 Technical Report ANL-80-74 Argonne National Laboratory
Powell M J D (1970) A hybrid method for nonlinear algebraic equations Numerical Methods for Nonlinear Algebraic Equations (ed P Rabinowitz) Gordon and Breach

5  Parameters

1:     FCN – SUBROUTINE, supplied by the user.External Procedure
Depending upon the value of IFLAG, FCN must either return the values of the functions fi  at a point x or return the Jacobian at x.
The specification of FCN is:
SUBROUTINE FCN ( N, X, FVEC, FJAC, IUSER, RUSER, IFLAG)
INTEGER  N, IUSER(*), IFLAG
REAL (KIND=nag_wp)  X(N), FVEC(N), FJAC(N,N), RUSER(*)
1:     N – INTEGERInput
On entry: n, the number of equations.
2:     X(N) – REAL (KIND=nag_wp) arrayInput
On entry: the components of the point x at which the functions or the Jacobian must be evaluated.
3:     FVEC(N) – REAL (KIND=nag_wp) arrayInput/Output
On entry: if IFLAG=2 , FVEC contains the function values fix  and must not be changed.
On exit: if IFLAG=1  on entry, FVEC must contain the function values fix  (unless IFLAG is set to a negative value by FCN).
4:     FJAC(N,N) – REAL (KIND=nag_wp) arrayInput/Output
On entry: if IFLAG=1 , FJAC contains the value of fi xj  at the point x, for i=1,2,,n and j=1,2,,n, and must not be changed.
On exit: if IFLAG=2  on entry, FJACij  must contain the value of fi xj  at the point x, for i=1,2,,n and j=1,2,,n, (unless IFLAG is set to a negative value by FCN).
5:     IUSER(*) – INTEGER arrayUser Workspace
6:     RUSER(*) – REAL (KIND=nag_wp) arrayUser Workspace
FCN is called with the parameters IUSER and RUSER as supplied to C05RBF. You are free to use the arrays IUSER and RUSER to supply information to FCN as an alternative to using COMMON global variables.
7:     IFLAG – INTEGERInput/Output
On entry: IFLAG=1 or 2.
IFLAG=1
FVEC is to be updated.
IFLAG=2
FJAC is to be updated.
On exit: in general, IFLAG should not be reset by FCN. If, however, you wish to terminate execution (perhaps because some illegal point X has been reached), then IFLAG should be set to a negative integer.
FCN must either be a module subprogram USEd by, or declared as EXTERNAL in, the (sub)program from which C05RBF is called. Parameters denoted as Input must not be changed by this procedure.
2:     N – INTEGERInput
On entry: n, the number of equations.
Constraint: N>0 .
3:     X(N) – REAL (KIND=nag_wp) arrayInput/Output
On entry: an initial guess at the solution vector.
On exit: the final estimate of the solution vector.
4:     FVEC(N) – REAL (KIND=nag_wp) arrayOutput
On exit: the function values at the final point returned in X.
5:     FJAC(N,N) – REAL (KIND=nag_wp) arrayOutput
On exit: the orthogonal matrix Q produced by the QR  factorization of the final approximate Jacobian.
6:     XTOL – REAL (KIND=nag_wp)Input
On entry: the accuracy in X to which the solution is required.
Suggested value: ε, where ε is the machine precision returned by X02AJF.
Constraint: XTOL0.0 .
7:     IUSER(*) – INTEGER arrayUser Workspace
8:     RUSER(*) – REAL (KIND=nag_wp) arrayUser Workspace
IUSER and RUSER are not used by C05RBF, but are passed directly to FCN and may be used to pass information to this routine as an alternative to using COMMON global variables.
9:     IFAIL – INTEGERInput/Output
On entry: IFAIL must be set to 0, -1​ or ​1. If you are unfamiliar with this parameter you should refer to Section 3.3 in the Essential Introduction for details.
For environments where it might be inappropriate to halt program execution when an error is detected, the value -1​ or ​1 is recommended. If the output of error messages is undesirable, then the value 1 is recommended. Otherwise, if you are not familiar with this parameter, the recommended value is 0. 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:
IFAIL=2
There have been at least 100 × N+1  evaluations of FCN. Consider restarting the calculation from the final point held in X.
IFAIL=3
No further improvement in the approximate solution X is possible; XTOL is too small.
IFAIL=4
The iteration is not making good progress. This failure exit may indicate that the system does not have a zero, or that the solution is very close to the origin (see Section 7). Otherwise, rerunning C05RBF from a different starting point may avoid the region of difficulty.
IFAIL=5
You have set IFLAG negative in FCN.
IFAIL=11
On entry, N0.
IFAIL=12
On entry, XTOL<0.0.
IFAIL=-999
Internal memory allocation failed.

7  Accuracy

If x^  is the true solution, C05RBF tries to ensure that
x-x^ 2 XTOL × x^ 2 .
If this condition is satisfied with XTOL = 10-k , then the larger components of x have k significant decimal digits. There is a danger that the smaller components of x may have large relative errors, but the fast rate of convergence of C05RBF usually obviates this possibility.
If XTOL is less than machine precision and the above test is satisfied with the machine precision in place of XTOL, then the routine exits with IFAIL=3.
Note:  this convergence test is based purely on relative error, and may not indicate convergence if the solution is very close to the origin.
The convergence test assumes that the functions and the Jacobian are coded consistently and that the functions are reasonably well behaved. If these conditions are not satisfied, then C05RBF may incorrectly indicate convergence. The coding of the Jacobian can be checked using C05ZDF. If the Jacobian is coded correctly, then the validity of the answer can be checked by rerunning C05RBF with a lower value for XTOL.

8  Further Comments

Local workspace arrays of fixed lengths are allocated internally by C05RBF. The total size of these arrays amounts to n×n+13/2 real elements.
The time required by C05RBF to solve a given problem depends on n, the behaviour of the functions, the accuracy requested and the starting point. The number of arithmetic operations executed by C05RBF is approximately 11.5×n2  to process each evaluation of the functions and approximately 1.3×n3  to process each evaluation of the Jacobian. The timing of C05RBF is strongly influenced by the time spent evaluating the functions.
Ideally the problem should be scaled so that, at the solution, the function values are of comparable magnitude.

9  Example

This example determines the values x1 , , x9  which satisfy the tridiagonal equations:
3-2x1x1-2x2 = -1, -xi-1+3-2xixi-2xi+1 = -1,  i=2,3,,8 -x8+3-2x9x9 = -1.

9.1  Program Text

Program Text (c05rbfe.f90)

9.2  Program Data

None.

9.3  Program Results

Program Results (c05rbfe.r)


C05RBF (PDF version)
C05 Chapter Contents
C05 Chapter Introduction
NAG Library Manual

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