Søren Faurby <soren.faurby <at> biology.au.dk> writes:
>
> In an effort to select the most appropriate number of clusters in a
> mixture analysis I am comparing the expected and actual membership of
> individuals in various clusters using the Fisher?s exact test. I aim
> for the model with the lowest possible p-value, but I frequently get
> p-values below 2.2e-16 and therefore does not get exact p-values with
> standard Fisher?s exact tests in R.
>
The p<2.2e-16 is a printing issue, not a precision issue.
> ff = fisher.test(dat3, workspace=30000000)
> ff
Fisher's Exact Test for Count Data
data: dat3
p-value < 2.2e-16
alternative hypothesis: two.sided
> str(ff)
List of 4
$ p.value : num 5.88e-58
$ alternative: chr "two.sided"
$ method : chr "Fisher's Exact Test for Count Data"
$ data.name : chr "dat3"
- attr(*, "class")= chr "htest"
So just use ff$p.value
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