robustrank (version 2024.1-28)

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

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)

Value

A p value for now.

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.

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)