# runs.test: Runs Test In tseries: Time Series Analysis and Computational Finance

 runs.test 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.

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)
```

tseries documentation built on Oct. 10, 2022, 5:06 p.m.