Dear R users,

I have a matrix a and a classification vector b such that

> str(a)
num [1:50, 1:800000]
and
> str(b)
Factor w/ 3 levels "cond1","cond2","cond3"

I'd like to do an anova on all 800000 columns and record the F statistic for
each test; I currently do this using

f.stat.vec <- numeric(length(a[1,])

for (i in 1:length(a[1,]) {
  f.test.frame <- data.frame(nums = a[,i], cond = b)
  aov.vox <- aov(nums ~ cond, data = f.test.frame)
  f.stat <- summary(aov.vox)[[1]][1,4]
  f.stat.vec[i] <- f.stat
}

The problem is that this code takes about 70 minutes to run.

Is there a faster way to do an anova & record the F stat for each column?

Any help would be appreciated.

Thanks
Heath

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