NSM3: cNWWM – R documentation

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cNWWM

Computes a critical value for the Nemenyi, Wilcoxon-Wilcox, Miller R* distribution.

Description

This function computes the critical value for the Nemenyi, Wilcoxon-Wilcox, Miller R* distribution at (or typically in the "Exact" and "Monte Carlo" cases, close to) the given alpha level.

Usage

cNWWM(alpha, k, n, method=NA, n.mc=10000)

Arguments

`alpha`	A numeric value between 0 and 1.
`k`	A numeric value indicating the number of treatments.
`n`	A numeric value indicating the number of blocks.
`method`	Either "Exact", "Monte Carlo" or "Asymptotic", indicating the desired distribution. When method=NA, "Exact" will be used if the number of permutations is 10,000 or less. Otherwise, "Monte Carlo" will be used.
`n.mc`	If method="Monte Carlo", the number of Monte Carlo samples used to estimate the distribution. Otherwise, not used.

Value

Returns a list with "NSM3Ch7c" class containing the following components:

`k`	number of treatments
`n`	number of blocks
`cutoff.U`	upper tail cutoff at or below user-specified alpha
`true.alpha.U`	true alpha level corresponding to cutoff.U (if method="Exact" or "Monte Carlo")

Author(s)

Grant Schneider

Examples

##Hollander-Wolfe-Chicken Example 7.4 Stuttering Adaptation
#cNWWM(.0492, 3, 18, "Monte Carlo") 
cNWWM(.0492, 3, 18, method="Monte Carlo",n.mc=2500) 
##Comment 7.35
cNWWM(.0093, 3, 3, "Exact")
#cNWWM(.0093, 3, 3, "Monte Carlo")

NSM3

Functions and Datasets to Accompany Hollander, Wolfe, and Chicken - Nonparametric Statistical Methods, Third Edition

v1.16

GPL-2

Authors

Grant Schneider, Eric Chicken, Rachel Becvarik

Initial release

2021-04-05