tseries (version 0.10-17)

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:
  • statisticthe value of the test statistic.
  • p.valuethe p-value of the test.
  • methoda character string indicating what type of test was performed.
  • data.namea character string giving the name of the data.
  • alternativea 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

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

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

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