cWNMT | R Documentation |
This function computes the critical value for the Wilcoxon, Nemenyi, McDonald-Thompson R distribution at (or typically in the "Exact" and "Monte Carlo" cases, close to) the given alpha level.
cWNMT(alpha, k, n, method=NA, n.mc=10000)
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. |
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") |
Grant Schneider
##Hollander-Wolfe-Chicken Example 7.3 Rounding First Base
#cWNMT(.047, 3, 15)
cWNMT(.047, 3, 15,n.mc=5000)
##Chapter 7 Comment 26
#cWNMT(.083, 4, 2)
cWNMT(.083, 4, 2,n.mc=5000)
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