# 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:

the value of the test statistic.

the p-value of the test.

a character string indicating what type of test was performed.

a character string giving the name of the data.

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

```
# NOT RUN {
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 0.10-47, License: GPL-2*