NAG Library Function Document

nag_zero_nonlin_eqns_deriv_rcomm (c05rdc)

▸▿ Contents

1 Purpose

2 Specification

3 Description

4 References

5 Arguments

6 Error Indicators and Warnings

7 Accuracy

8 Parallelism and Performance

9 Further Comments

▸▿ 10 Example

10.1 Program Text

10.2 Program Data

10.3 Program Results

1 Purpose

nag_zero_nonlin_eqns_deriv_rcomm (c05rdc) is a comprehensive reverse communication function 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

#include <nag.h>

#include <nagc05.h>

void	nag_zero_nonlin_eqns_deriv_rcomm (Integer irevcm, Integer n, double x[], double fvec[], double fjac[], double xtol, Nag_ScaleType scale_mode, double diag[], double factor, double r[], double qtf[], Integer iwsav[], double rwsav[], NagError fail)

3 Description

The system of equations is defined as:

f_{i} (x_{1}, x_{2}, \dots, x_{n}) = 0, i = 1, 2, \dots, n .

nag_zero_nonlin_eqns_deriv_rcomm (c05rdc) is based on the MINPACK routine HYBRJ (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. 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 Arguments

Note: this function uses reverse communication. Its use involves an initial entry, intermediate exits and re-entries, and a final exit, as indicated by the argument irevcm. Between intermediate exits and re-entries, all arguments other than fvec and fjac must remain unchanged.

1: $irevcm$ – Integer *Input/Output

On initial entry: must have the value

0

On intermediate exit: specifies what action you must take before re-entering nag_zero_nonlin_eqns_deriv_rcomm (c05rdc) with irevcm unchanged. The value of irevcm should be interpreted as follows:

$irevcm = 1$: Indicates the start of a new iteration. No action is required by you, but x and fvec are available for printing.
$irevcm = 2$: Indicates that before re-entry to nag_zero_nonlin_eqns_deriv_rcomm (c05rdc), fvec must contain the function values $f_{i} (x)$ .
$irevcm = 3$: Indicates that before re-entry to nag_zero_nonlin_eqns_deriv_rcomm (c05rdc), $fjac [(j - 1) \times n + i - 1]$ must contain the value of $\frac{\partial f_{i}}{\partial x_{j}}$ at the point $x$ , for $i = 1, 2, \dots, n$ and $j = 1, 2, \dots, n$ .

On final exit:

irevcm = 0

, and the algorithm has terminated.

Constraint:

irevcm = 0

1

2

3

2: $n$ – IntegerInput

On entry:

n

, the number of equations.

Constraint:

n > 0

3: $x [n]$ – doubleInput/Output

On initial entry: an initial guess at the solution vector.

On intermediate exit: contains the current point.

On final exit: the final estimate of the solution vector.

4: $fvec [n]$ – doubleInput/Output

On initial entry: need not be set.

On intermediate re-entry: if

irevcm \neq 2

, fvec must not be changed.

irevcm = 2

, fvec must be set to the values of the functions computed at the current point x.

On final exit: the function values at the final point, x.

5: $fjac [n \times n]$ – doubleInput/Output

Note: the

(i, j)

th element of the matrix is stored in

fjac [(j - 1) \times n + i - 1]

On initial entry: need not be set.

On intermediate re-entry: if

irevcm \neq 3

, fjac must not be changed.

irevcm = 3

fjac [(j - 1) \times n + i - 1]

must contain the value of

\frac{\partial f_{i}}{\partial x_{j}}

at the point

x

, for

i = 1, 2, \dots, n

and

j = 1, 2, \dots, n

On final exit: the orthogonal matrix

Q

produced by the

Q R

factorization of the final approximate Jacobian, stored by columns.

6: $xtol$ – doubleInput

On initial entry: the accuracy in x to which the solution is required.

Suggested value:

\sqrt{ε}

, where

ε

is the machine precision returned by nag_machine_precision (X02AJC).

Constraint:

xtol \geq 0.0

7: $scale_mode$ – Nag_ScaleTypeInput

On initial entry: indicates whether or not you have provided scaling factors in diag.

scale_mode = Nag_ScaleProvided

the scaling must have been supplied in diag.

Otherwise, if

scale_mode = Nag_NoScaleProvided

, the variables will be scaled internally.

Constraint:

scale_mode = Nag_NoScaleProvided

Nag_ScaleProvided

8: $diag [n]$ – doubleInput/Output

On initial entry: if

scale_mode = Nag_ScaleProvided

, diag must contain multiplicative scale factors for the variables.

scale_mode = Nag_NoScaleProvided

, diag need not be set.

Constraint: if

scale_mode = Nag_ScaleProvided

diag [i - 1] > 0.0

, for

i = 1, 2, \dots, n

On intermediate exit: diag must not be changed.

On final exit: the scale factors actually used (computed internally if

scale_mode = Nag_NoScaleProvided

9: $factor$ – doubleInput

On initial entry: a quantity to be used in determining the initial step bound. In most cases, factor should lie between

0.1

and

100.0

. (The step bound is

factor \times {‖diag \times x‖}_{2}

if this is nonzero; otherwise the bound is factor.)

Suggested value:

factor = 100.0

Constraint:

factor > 0.0

10: $r [n \times (n + 1) / 2]$ – doubleInput/Output

On initial entry: need not be set.

On intermediate exit: must not be changed.

On final exit: the upper triangular matrix

R

produced by the

Q R

factorization of the final approximate Jacobian, stored row-wise.

11: $qtf [n]$ – doubleInput/Output

On initial entry: need not be set.

On intermediate exit: must not be changed.

On final exit: the vector

Q^{T} f

12: $iwsav [17]$ – IntegerCommunication Array

13: $rwsav [4 \times n + 10]$ – doubleCommunication Array

The arrays iwsav and rwsav MUST NOT be altered between calls to nag_zero_nonlin_eqns_deriv_rcomm (c05rdc).

14: $fail$ – NagError *Input/Output

The NAG error argument (see Section 3.6 in the Essential Introduction).

6 Error Indicators and Warnings

NE_ALLOC_FAIL: Dynamic memory allocation failed.
See Section 3.2.1.2 in the Essential Introduction for further information.
NE_BAD_PARAM: On entry, argument $〈value〉$ had an illegal value.
NE_DIAG_ELEMENTS: On entry, $scale_mode = Nag_ScaleProvided$ and diag contained a non-positive element.
NE_INT: On entry, $irevcm = 〈value〉$ .
Constraint: $irevcm = 0$ , $1$ , $2$ or $3$ .

On entry, $n = 〈value〉$ .
Constraint: $n > 0$ .
NE_INTERNAL_ERROR: An internal error has occurred in this function. Check the function call and any array sizes. If the call is correct then please contact NAG for assistance.

An unexpected error has been triggered by this function. Please contact NAG.
See Section 3.6.6 in the Essential Introduction for further information.
NE_NO_IMPROVEMENT: The iteration is not making good progress, as measured by the improvement from the last $〈value〉$ iterations. 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 nag_zero_nonlin_eqns_deriv_rcomm (c05rdc) from a different starting point may avoid the region of difficulty.

The iteration is not making good progress, as measured by the improvement from the last $〈value〉$ Jacobian evaluations. 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 nag_zero_nonlin_eqns_deriv_rcomm (c05rdc) from a different starting point may avoid the region of difficulty.
NE_NO_LICENCE: Your licence key may have expired or may not have been installed correctly.
See Section 3.6.5 in the Essential Introduction for further information.
NE_REAL: On entry, $factor = 〈value〉$ .
Constraint: $factor > 0.0$ .

On entry, $xtol = 〈value〉$ .
Constraint: $xtol \geq 0.0$ .
NE_TOO_SMALL: No further improvement in the solution is possible. xtol is too small: $xtol = 〈value〉$ .

7 Accuracy

\hat{x}

is the true solution and

D

denotes the diagonal matrix whose entries are defined by the array diag, then nag_zero_nonlin_eqns_deriv_rcomm (c05rdc) tries to ensure that

{‖D (x - \hat{x})‖}_{2} \leq xtol \times {‖D \hat{x}‖}_{2} .

If this condition is satisfied with

xtol = 10^{- k}

, then the larger components of

D x

have

k

significant decimal digits. There is a danger that the smaller components of

D x

may have large relative errors, but the fast rate of convergence of nag_zero_nonlin_eqns_deriv_rcomm (c05rdc) 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 function exits with

fail . code =

NE_TOO_SMALL.

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 nag_zero_nonlin_eqns_deriv_rcomm (c05rdc) may incorrectly indicate convergence. The coding of the Jacobian can be checked using nag_check_derivs (c05zdc). If the Jacobian is coded correctly, then the validity of the answer can be checked by rerunning nag_zero_nonlin_eqns_deriv_rcomm (c05rdc) with a lower value for xtol.

8 Parallelism and Performance

nag_zero_nonlin_eqns_deriv_rcomm (c05rdc) is threaded by NAG for parallel execution in multithreaded implementations of the NAG Library.

nag_zero_nonlin_eqns_deriv_rcomm (c05rdc) 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 function. Please also consult the Users' Note for your implementation for any additional implementation-specific information.

9 Further Comments

The time required by nag_zero_nonlin_eqns_deriv_rcomm (c05rdc) 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 nag_zero_nonlin_eqns_deriv_rcomm (c05rdc) is approximately

11.5 \times n^{2}

to process each evaluation of the functions and approximately

1.3 \times n^{3}

to process each evaluation of the Jacobian. The timing of nag_zero_nonlin_eqns_deriv_rcomm (c05rdc) 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.