R: Runs Test

runs.test {tseries} | R Documentation

## Runs Test

### Description

Computes the runs test for randomness of the dichotomous (binary) data series `x`.

### Usage

    runs.test(x, alternative = c("two.sided", "less", "greater"))

### Arguments

`x` | a dichotomous factor.
`alternative` | indicates the alternative hypothesis and must be one of `"two.sided"` (default), `"less"`, or `"greater"`. You can specify just the initial letter.

### Details

This test searches for randomness in the observed data series `x` by examining the frequency of runs. A "run" is defined as a series of similar responses.

Note, that by using the alternative `"less"` the null of randomness is tested against some kind of "under-mixing" ("trend"). By using the alternative `"greater"` the null of randomness is tested against some kind of "over-mixing" ("mean-reversion").

Missing values are not allowed.

### Value

A list with class `"htest"` containing the following components:

`statistic` | the value of the test statistic.
`p.value` | the p-value of the test.
`method` | a character string indicating what type of test was performed.
`data.name` | a character string giving the name of the data.
`alternative` | a character string describing the alternative hypothesis.

### Author(s)

A. Trapletti

### References

S. Siegel (1956): Nonparametric Statistics for the Behavioural Sciences, McGraw-Hill, New York.

S. Siegel and N. J. Castellan (1988): Nonparametric Statistics for the Behavioural Sciences, 2nd edn, McGraw-Hill, New York.

### Examples

    x <- factor(sign(rnorm(100)))  # randomness
    runs.test(x)

    x <- factor(rep(c(-1,1),50))  # over-mixing
    runs.test(x)

[Package tseries version 0.10-47 Index]