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Computes the runs test for randomness of the dichotomous (binary) data
series x
.
runs.test(x, alternative = c("two.sided", "less", "greater"))
a dichotomous factor.
indicates the alternative hypothesis and must be
one of "two.sided"
(default), "less"
, or
"greater"
. You can specify just the initial letter.
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.
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.
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.
# NOT RUN {
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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