# runs.test

##### Runs Test

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

.

- Keywords
- ts

##### 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.

##### 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)
```

*Documentation reproduced from package tseries, version 0.10-1, License: GPL (see file COPYING)*