| cNWWM {NSM3} | R Documentation |
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")