nag_rand_sample (g05ndc) (PDF version)
g05 Chapter Contents
g05 Chapter Introduction
NAG Library Manual

NAG Library Function Document

nag_rand_sample (g05ndc)

+ Contents

    1  Purpose
    7  Accuracy

1  Purpose

nag_rand_sample (g05ndc) selects a pseudorandom sample without replacement from an integer vector.

2  Specification

#include <nag.h>
#include <nagg05.h>
void  nag_rand_sample (const Integer ipop[], Integer n, Integer isampl[], Integer m, Integer state[], NagError *fail)

3  Description

nag_rand_sample (g05ndc) selects m elements from a population vector ipop of length n and places them in a sample vector isampl. Their order in ipop will be preserved in isampl. Each of the n m  possible combinations of elements of isampl may be regarded as being equally probable.
For moderate or large values of n it is theoretically impossible that all combinations of size m may occur, unless m is near 1 or near n. This is because n m  exceeds the cycle length of any of the base generators. For practical purposes this is irrelevant, as the time taken to generate all possible combinations is many millenia.
One of the initialization functions nag_rand_init_repeatable (g05kfc) (for a repeatable sequence if computed sequentially) or nag_rand_init_nonrepeatable (g05kgc) (for a non-repeatable sequence) must be called prior to the first call to nag_rand_sample (g05ndc).

4  References

Kendall M G and Stuart A (1969) The Advanced Theory of Statistics (Volume 1) (3rd Edition) Griffin
Knuth D E (1981) The Art of Computer Programming (Volume 2) (2nd Edition) Addison–Wesley

5  Arguments

1:     ipop[n]const IntegerInput
On entry: the population to be sampled.
2:     nIntegerInput
On entry: the number of elements in the population vector to be sampled.
Constraint: n1.
3:     isampl[m]IntegerOutput
On exit: the selected sample.
4:     mIntegerInput
On entry: the sample size.
Constraint: 1mn.
5:     state[dim]IntegerCommunication Array
Note: the dimension, dim, of this array is dictated by the requirements of associated functions that must have been previously called. This array MUST be the same array passed as argument state in the previous call to nag_rand_init_repeatable (g05kfc) or nag_rand_init_nonrepeatable (g05kgc).
On entry: contains information on the selected base generator and its current state.
On exit: contains updated information on the state of the generator.
6:     failNagError *Input/Output
The NAG error argument (see Section 3.6 in the Essential Introduction).

6  Error Indicators and Warnings

NE_BAD_PARAM
On entry, argument value had an illegal value.
NE_INT
On entry, n=value.
Constraint: n1.
NE_INT_2
On entry, m=value and n=value.
Constraint: 1mn.
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.
NE_INVALID_STATE
On entry, state vector has been corrupted or not initialized.

7  Accuracy

Not applicable.

8  Parallelism and Performance

Not applicable.

9  Further Comments

The time taken by nag_rand_sample (g05ndc) is of order n.
In order to sample other kinds of vectors, or matrices of higher dimension, the following technique may be used:
(a) set ipop[i-1]=i, for i=1,2,,n;
(b) use nag_rand_sample (g05ndc) to take a sample from ipop and put it into isampl;
(c) use the contents of isampl as a set of indices to access the relevant vector or matrix.
In order to divide a population into several groups, nag_rand_permute (g05ncc) is more efficient.

10  Example

In the example program random samples of size 1,2,,8 are selected from a vector containing the first eight positive integers in ascending order. The samples are generated and printed for each sample size by a call to nag_rand_sample (g05ndc) after initialization by nag_rand_init_repeatable (g05kfc).

10.1  Program Text

Program Text (g05ndce.c)

10.2  Program Data

None.

10.3  Program Results

Program Results (g05ndce.r)


nag_rand_sample (g05ndc) (PDF version)
g05 Chapter Contents
g05 Chapter Introduction
NAG Library Manual

© The Numerical Algorithms Group Ltd, Oxford, UK. 2014