tseries (version 0.10-47)

runs.test: 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.

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.

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.

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)
# }