Fast version of Fisher's Exact Test

Do you mean a test something such as this?
fisher.test(matrix(c(502,498,490, 510), nrow = 2))
Fisher's Exact Test for Count Data

data:  matrix(c(502, 498, 490, 510), nrow = 2) 
p-value = 0.6228
alternative hypothesis: true odds ratio is not equal to 1 
95 percent confidence interval:
 0.8770113 1.2550998 
sample estimates:
odds ratio 
  1.049119 

This runs quickly on my machine.
system.time(fisher.test(matrix(c(502,498,490, 510), nrow = 2)))
user  system elapsed 
  0.008   0.001   0.010
sessionInfo()
R version 2.12.2 (2011-02-25)
Platform: x86_64-apple-darwin9.8.0/x86_64 (64-bit)

locale:
[1] en_CA.UTF-8/en_CA.UTF-8/C/C/en_CA.UTF-8/en_CA.UTF-8

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base     

loaded via a namespace (and not attached):
[1] tools_2.12.2

Can you provide an example that is running slowly for you?

Steven McKinney
Is anyone aware of a fast way of doing fisher's exact test for a series of 2
x 2 tables in R? The fisher.test is really slow if n1=1000 and n2 = 1000.

--
Thanks,
Jim.

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