[R] Duncan's MRT: limitations to qtukey() function?

[Andrea Onofri]

Dear all,

I'm using R to perform multiple comparison testing on agriculture 
genotype trials. To perform  the Duncan's MRT, I use the qtukey() 
function with the following syntax:

qtukey(p = ((1 - 0.05) ^ (pos - 1)), nmeans = pos, df = ni)

I experience a strange behaviour when the number of means in the trial 
and the number of residual degrees of freedom (ni) becomes high 
(orientatively pos > 30 and ni > 60), i.e. the function returns NaN 
together with the following message:

convergence failed in 'qtukey'

Running the code below should reproduce a  statistical table for 
Duncan's MRT, such those reported on old books of agricultural 
statistics (ex. Steel and Torrie, 1960).

table <- matrix(0, 28, 14)
pos <- c(10, 12, 14, 16, 18, 20, 22, 24, 26, 28, 30, 50, 100, 200)
df <- c(2:20, seq(22, 30, by = 2), 40, 60, 100, 1000)
for (i in 1:28) table [i, ] <- qtukey(p = ((1 - 0.05) ^ (pos - 1)), 
nmeans = pos, df = df[i])
colnames(table) <- pos
rownames(table) <- df

Indeed, I get several NaN and some odd figures.

Am I doing something wrong or is there any intrinsic limit for the 
values of p, nmeans and df within the qtukey() function? Just in this 
latter case, is it possible to raise those limits? Some genotype trials 
can have more than thirty treatments  under comparison.

I thank you all for your attention.

Andrea Onofri
Department of Agriculture and Environmental Sciences
University of Perugia (ITALY)