mod.wmw.test: Modified Wilcoxon-Mann-Whitney Test

In robustrank: Robust Rank-Based Tests

Description

Also known as the Fligner-Policello test.

Usage

mod.wmw.test(X, Y, alternative = c("two.sided", "less", "greater"),
         correct = TRUE, perm = NULL, mc.rep = 10000, method =
         c("combine", "comb2", "fp", "wmw", "fplarge", "nsm3"),
         verbose = FALSE, mode = c("test", "var"), useC = TRUE)

Arguments

X	Samples from population 1.
Y	Samples from population 2.
alternative	Directon of the alternative hypothesis.
correct	Whether to do continutiy correction.
perm	Boolean, whether to do permutation to get p-value or use normal approximation. See details.
mc.rep	Default number of replicates when doing permutation. See details.
method	For development.
verbose	For development. Print some debug info.
mode	For development.
useC	For development. Run C or R implementation.

Details

When perm is null, we will compute permutation-based p values if either sample size is less than 20 and compute normal approximation-based p values otherwise. When doing permuation, if the possible number of combinations is less than mc.rep, every possible configuration is done.

Value

A p value for now.

References

manuscript in preperation

Examples

# Example 4.1, Hollander, Wolfe and Chicken (2014) Nonparameteric Statistics
X <- c(0.80, 0.83, 1.89, 1.04, 1.45, 1.38, 1.91, 1.64, 0.73, 1.46)
Y <- c(1.15, 0.88, 0.90, 0.74, 1.21)
mod.wmw.test(X, Y, method="wmw", alternative="greater")
mod.wmw.test(X, Y, method="combine", alternative="greater", verbose=1)

# Section 4.1 Problem 1, Hollander et al. 
X=c(1651,1112,102.4,100,67.6,65.9,64.7,39.6,31.0)
Y=c(48.1,48.0,45.5,41.7,35.4,34.3,32.4,29.1,27.3,18.9,6.6,5.2,4.7)
mod.wmw.test(X, Y, method="wmw")
mod.wmw.test(X, Y, method="combine", verbose=1)

# Section 4.1 Problem 5, Hollander et al. 
X=c(12 ,44 ,34 ,14 ,9  ,19 ,156,23 ,13 ,11 ,47 ,26 ,14 ,33 ,15 ,62 ,5  ,8  ,0  ,154,146)
Y=c(37,39,30,7,13,139, 45,25,16,146,94,16,23,1,290,169,62,145,36, 20, 13)
mod.wmw.test(X, Y, method="wmw", alternative="less")
mod.wmw.test(X, Y, method="combine", alternative="less", verbose=1)

# Section 4.1 Problem 15, Hollander et al. 
X=c(0.19,0.14,0.02,0.44,0.37)
Y=c(0.89,0.76,0.63,0.69,0.58,0.79,0.02,0.79)
mod.wmw.test(X, Y, method="wmw")
mod.wmw.test(X, Y, method="combine", verbose=1)

# Table 4.7, Hollander et al. 
X=c(297,340,325,227,277,337,250,290)
Y=c(293,291,289,430,510,353,318)
mod.wmw.test(X, Y, method="wmw", alternative="less")
mod.wmw.test(X, Y, method="combine", alternative="less", verbose=1)

robustrank documentation built on July 15, 2020, 5:08 p.m.