The R_TEST function tests the hypothesis that a binary population (a sequence of 1s and 0s) represents a “random sampling”.

This routine is written in the IDL language. Its source code can be found in the file r_test.pro in the lib subdirectory of the IDL distribution.

## Examples

`; Define a binary population:X = [0, 1, 1, 0, 1, 0, 0, 0, 1, 0, 0, 1, 1, 0, 1, 0, 1, 0, 0, \$   1, 0, 1, 1, 0, 1, 0, 0, 1, 0, 1]; Test the hypothesis that X represents a random sampling against; the hypothesis that it does not represent a random sampling at; the 0.05 significance level:result = R_TEST(X, R = r, N0 = n0, N1 = n1)PRINT, result`

IDL prints:

`[2.26487, 0.0117604]`

Print the values of the keyword parameters:

`PRINT, 'Runs: ', r & PRINT, 'Zeros: ', n0 & PRINT, 'Ones: ', n1`
`Runs:     22`
`Zeros:    16`
`Ones:     14`

The computed probability (0.0117604) is less than the 0.05 significance level and therefore we reject the hypothesis that X represents a random sampling. The results show that there are too many runs, indicating a non-random cyclical pattern.

## Syntax

Result = R_TEST( X [, N0=variable] [, N1=variable] [, R=variable] )

## Return Value

The result is a two-element vector containing the nearly-normal test statistic Z and its associated probability. This two-tailed test is based on the “theory of runs” and is often referred to as the “Runs Test for Randomness.”

## Arguments

### X

An n-element integer, single-, or double-precision floating-point vector. Elements not equal to 0 or 1 are removed and the length of X is correspondingly reduced.

## Keywords

### N0

Set this keyword to a named variable that will contain the number of 0s in X.

### N1

Set this keyword to a named variable that will contain the number of 1s in X.

### R

Set this keyword to a named variable that will contain the number of runs (clusters of 0s and 1s) in X.

## Version History

 4 Introduced