NAG Library Routine Document

g05ymf generates a uniformly distributed low-discrepancy sequence as proposed by Sobol, Faure or Niederreiter. It must be preceded by a call to one of the initialization routines g05ylf or g05ynf.

2

Specification

Fortran Interface

Subroutine g05ymf (

n, rcord, quas, ldquas, iref, ifail)

Integer, Intent (In)	::	n, rcord, ldquas
Integer, Intent (Inout)	::	iref(*), ifail
Real (Kind=nag_wp), Intent (Inout)	::	quas(ldquas,*)

C Header Interface

#include <nagmk26.h>

void	g05ymf_ (const Integer n, const Integer rcord, double quas[], const Integer ldquas, Integer iref[], Integer ifail)

3

Description

Low discrepancy (quasi-random) sequences are used in numerical integration, simulation and optimization. Like pseudorandom numbers they are uniformly distributed but they are not statistically independent, rather they are designed to give more even distribution in multidimensional space (uniformity). Therefore they are often more efficient than pseudorandom numbers in multidimensional Monte–Carlo methods.

g05ymf generates a set of points

x^{1}, x^{2}, \dots, x^{N}

with high uniformity in the

S

-dimensional unit cube

I^{S} = {[0, 1]}^{S}

Let

G

be a subset of

I^{S}

and define the counting function

S_{N} (G)

as the number of points

x^{i} \in G

. For each

x = (x_{1}, x_{2}, \dots, x_{S}) \in I^{S}

, let

G_{x}

be the rectangular

S

-dimensional region

G_{x} = [0, x_{1}) \times [0, x_{2}) \times \dots \times [0, x_{S})

with volume

x_{1}, x_{2}, \dots, x_{S}

. Then one measure of the uniformity of the points

x^{1}, x^{2}, \dots, x^{N}

is the discrepancy:

D_{N}^{*} (x^{1}, x^{2}, \dots, x^{N}) = \sup_{x \in I^{S}} |S_{N} (G_{x}) - N x_{1}, x_{2}, \dots, x_{S}| .

which has the form

D_{N}^{*} (x^{1}, x^{2}, \dots, x^{N}) \leq C_{S} {(\log N)}^{S} + O ({(\log N)}^{S - 1}) for all N \geq 2 .

The principal aim in the construction of low-discrepancy sequences is to find sequences of points in

I^{S}

with a bound of this form where the constant

C_{S}

is as small as possible.

The type of low-discrepancy sequence generated by g05ymf depends on the initialization routine called and can include those proposed by Sobol, Faure or Niederreiter. If the initialization routine g05ynf was used then the sequence will be scrambled (see Section 3 in g05ynf for details).

4

References

Bratley P and Fox B L (1988) Algorithm 659: implementing Sobol's quasirandom sequence generator ACM Trans. Math. Software 14(1) 88–100

Fox B L (1986) Algorithm 647: implementation and relative efficiency of quasirandom sequence generators ACM Trans. Math. Software 12(4) 362–376

5

Arguments

Note: the following variables are used in the parameter descriptions:

$idim = idim$ , the number of dimensions required, see g05ylf or g05ynf
$liref = liref$ , the length of iref as supplied to the initialization routine g05ylf or g05ynf

1: $n$ – IntegerInput

On entry: the number of quasi-random numbers required.

Constraint:

n \geq 0

and

n + previous number of generated values \leq 2^{31} - 1

2: $rcord$ – IntegerInput

On entry: the order in which the generated values are returned.

Constraint:

rcord = 1

2

3: $quas (ldquas *)$ – Real (Kind=nag_wp) arrayOutput

Note: the second dimension of the array quas must be at least

n

rcord = 1

and at least

idim

rcord = 2

On exit: contains the n quasi-random numbers of dimension idim.

rcord = 1

quas (i, j)

holds the

j

th value for the

i

th dimension.

rcord = 2

quas (i, j)

holds the

i

th value for the

j

th dimension.

4: $ldquas$ – IntegerInput

On entry: the first dimension of the array quas as declared in the (sub)program from which g05ymf is called.

Constraints:

if $rcord = 1$ , $ldquas \geq idim$ ;
if $rcord = 2$ , $ldquas \geq n$ .

5: $iref (*)$ – Integer arrayCommunication Array

Note: the dimension of the array iref must be at least

liref

On entry: contains information on the current state of the sequence.

On exit: contains updated information on the state of the sequence.

6: $ifail$ – IntegerInput/Output

On entry: ifail must be set to

0

- 1 or 1

. If you are unfamiliar with this argument you should refer to Section 3.4 in How to Use the NAG Library and its Documentation 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 argument, 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

- 1

, explanatory error messages are output on the current error message unit (as defined by x04aaf).

Errors or warnings detected by the routine:

$ifail = 1$: On entry, $n = 〈value〉$ .
Constraint: $n \geq 0$ .

On entry, value of n would result in too many calls to the generator: $n = 〈value〉$ , generator has previously been called $〈value〉$ times.

$ifail = 2$: On entry, $rcord = 〈value〉$ .
Constraint: $rcord = 1$ or $2$ .

$ifail = 4$: On entry, $ldquas = 〈value〉$ , $idim = 〈value〉$ .
Constraint: if $rcord = 1$ , $ldquas \geq idim$ .

On entry, $ldquas = 〈value〉$ and $n = 〈value〉$ .
Constraint: if $rcord = 2$ , $ldquas \geq n$ .

$ifail = 5$: On entry, iref has either not been initialized or has been corrupted.

$ifail = - 99$: An unexpected error has been triggered by this routine. Please contact NAG.
See Section 3.9 in How to Use the NAG Library and its Documentation for further information.

$ifail = - 399$: Your licence key may have expired or may not have been installed correctly.
See Section 3.8 in How to Use the NAG Library and its Documentation for further information.

$ifail = - 999$: Dynamic memory allocation failed.
See Section 3.7 in How to Use the NAG Library and its Documentation for further information.

7

Accuracy

Not applicable.

8

Parallelism and Performance

g05ymf is threaded by NAG for parallel execution in multithreaded implementations of the NAG Library.

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 Sobol, Sobol (A659) and Niederreiter quasi-random number generators in g05ymf have been parallelized, but require quite large problem sizes to see any significant performance gain. Parallelism is only enabled when

rcord = 2

. The Faure generator is serial.

9

Further Comments

None.

10

Example

This example calls g05ylf and g05ymf to estimate the value of the integral

\int_{0}^{1} \dots \int_{0}^{1} \prod_{i = 1}^{s} |4 x_{i} - 2| d x_{1}, d x_{2}, \dots, d x_{s} = 1 .

In this example the number of dimensions

S

is set to

8

NAG Library Routine Document

g05ymf (quasi_uniform)

▸▿ 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