NAG Library Function Document

nag_quasi_rand_lognormal (g05ykc)

 Contents

    1  Purpose
    7  Accuracy

1
Purpose

nag_quasi_rand_lognormal (g05ykc) generates a quasi-random sequence from a log-normal distribution. It must be preceded by a call to one of the initialization functions nag_quasi_init (g05ylc) or nag_quasi_init_scrambled (g05ync).

2
Specification

#include <nag.h>
#include <nagg05.h>
void  nag_quasi_rand_lognormal (Nag_OrderType order, const double xmean[], const double std[], Integer n, double quas[], Integer pdquas, Integer iref[], NagError *fail)

3
Description

nag_quasi_rand_lognormal (g05ykc) generates a quasi-random sequence from a log-normal distribution by first generating a uniform quasi-random sequence which is then transformed into a log-normal sequence using the exponential of the inverse of the Normal CDF. The type of uniform sequence used depends on the initialization function called and can include the low-discrepancy sequences proposed by Sobol, Faure or Niederreiter. If the initialization function nag_quasi_init_scrambled (g05ync) was used then the underlying uniform sequence is first scrambled prior to being transformed (see Section 3 in nag_quasi_init_scrambled (g05ync) 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
Wichura (1988) Algorithm AS 241: the percentage points of the Normal distribution Appl. Statist. 37 477–484

5
Arguments

Note: the following variables are used in the parameter descriptions:
1:     order Nag_OrderTypeInput
On entry: the order argument specifies the two-dimensional storage scheme being used, i.e., row-major ordering or column-major ordering. C language defined storage is specified by order=Nag_RowMajor. See Section 3.3.1.3 in How to Use the NAG Library and its Documentation for a more detailed explanation of the use of this argument.
Constraint: order=Nag_RowMajor or Nag_ColMajor.
2:     xmean[idim] const doubleInput
On entry: specifies, for each dimension, the mean of the underlying Normal distribution.
Constraint: xmean[i-1] - lognag_real_safe_small_number -10.0× std[i-1] , for i=1,2,,idim.
3:     std[idim] const doubleInput
On entry: specifies, for each dimension, the standard deviation of the underlying Normal distribution.
Constraint: std[i-1]0.0, for i=1,2,,idim.
4:     n IntegerInput
On entry: the number of quasi-random numbers required.
Constraint: n0 and n+previous number of generated values231-1.
5:     quas[dim] doubleOutput
Note: the dimension, dim, of the array quas must be at least pdquas×idim.
The dimension, dim, of the array quas must be at least
  • max1,pdquas×idim when order=Nag_ColMajor;
  • max1,n×pdquas when order=Nag_RowMajor.
Where QUASi,j appears in this document, it refers to the array element
  • quas[j-1×pdquas+i-1] when order=Nag_ColMajor;
  • quas[i-1×pdquas+j-1] when order=Nag_RowMajor.
On exit: QUASi,j holds the ith value for the jth dimension.
6:     pdquas IntegerInput
On entry: the stride separating row or column elements (depending on the value of order) in the array quas.
Constraints:
  • if order=Nag_ColMajor, pdquasn;
  • if order=Nag_RowMajor, pdquasidim.
7:     iref[liref] IntegerCommunication Array
On entry: contains information on the current state of the sequence.
On exit: contains updated information on the state of the sequence.
8:     fail NagError *Input/Output
The NAG error argument (see Section 3.7 in How to Use the NAG Library and its Documentation).

6
Error Indicators and Warnings

NE_ALLOC_FAIL
Dynamic memory allocation failed.
See Section 2.3.1.2 in How to Use the NAG Library and its Documentation for further information.
NE_BAD_PARAM
On entry, argument value had an illegal value.
NE_INITIALIZATION
On entry, iref has either not been initialized or has been corrupted.
NE_INT
On entry, n=value.
Constraint: n0.
NE_INT_2
On entry, pdquas=value and idim=value.
Constraint: pdquasidim.
On entry, pdquas=value and n=value.
Constraint: pdquasn.
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.
See Section 2.7.6 in How to Use the NAG Library and its Documentation for further information.
NE_NO_LICENCE
Your licence key may have expired or may not have been installed correctly.
See Section 2.7.5 in How to Use the NAG Library and its Documentation for further information.
NE_REAL_ARRAY
On entry, at least one element of xmean is too large, xmean[value]=value.
Constraint: xmean[i]value.
On entry, std[value]=value.
Constraint: std[i]0.
NE_TOO_MANY_CALLS
There have been too many calls to the generator.

7
Accuracy

Not applicable.

8
Parallelism and Performance

nag_quasi_rand_lognormal (g05ykc) is threaded by NAG for parallel execution in multithreaded implementations of the NAG Library.
nag_quasi_rand_lognormal (g05ykc) 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.
The Sobol, Sobol (A659) and Niederreiter quasi-random number generators in g05ykc have been parallelized, but require quite large problem sizes to see any significant performance gain. Parallelism is only enabled when order=Nag_ColMajor. The Faure generator is serial.

9
Further Comments

None.

10
Example

This example calls nag_quasi_init (g05ylc) to initialize the generator and then nag_quasi_rand_lognormal (g05ykc) to produce a sequence of five four-dimensional quasi-random numbers variates.

10.1
Program Text

Program Text (g05ykce.c)

10.2
Program Data

None.

10.3
Program Results

Program Results (g05ykce.r)

© The Numerical Algorithms Group Ltd, Oxford, UK. 2017