rmd.test: Ratio Mean Deviance Test

In jmuOutlier: Permutation Tests for Nonparametric Statistics

Description

A permutation test is performed based on the estimated RMD, the ratio of the mean of the absolute value of the deviances, for data x and y.

Usage

rmd.test(x, y, alternative = c("two.sided", "less", "greater"), all.perms = TRUE, 
         num.sim = 20000)

Arguments

x	Numeric vector of data values.
y	Numeric vector of data values.
alternative	A character string specifying the alternative hypothesis, and must be one of "two.sided" (default), "greater" or "less". Only the initial letter needs to be specified.
all.perms	Logical. The exact p-value is attempted when all.perms (i.e., all permutations) is TRUE (default), and is simulated when all.perms is FALSE or when computing an exact p-value requires more than num.sim calculations.
num.sim	The upper limit on the number of permutations generated.

Value

alternative	Same as the input.
rmd.hat	The value of the RMD test statistic.
p.value	The p-value of the test.

Note

The formulas computed within rmd.test are based on the textbook by Higgins (2004).

Author(s)

Steven T. Garren, James Madison University, Harrisonburg, Virginia, USA

References

Higgins, J. J. (2004) Introduction to Modern Nonparametric Statistics.

See Also

ansari.test, siegel.test, and perm.test

Examples

rmd.test( c(13, 34, 2, 19, 49, 63), c(17, 29, 22) )
rmd.test( c(13, 34, 2, 19, 49, 63), c(17, 29, 22), "greater" )

Example output

[[1]]
[1] "Exact p-value was calculated."

$alternative
[1] "two.sided"

$rmd.hat
[1] 4.666667

$p.value
[1] 0.01190476

[[1]]
[1] "Exact p-value was calculated."

$alternative
[1] "greater"

$rmd.hat
[1] 4.666667

$p.value
[1] 0.01190476

jmuOutlier documentation built on Aug. 6, 2019, 1:03 a.m.