Relative abundance does what now!?

relAbund.R

# my "true community" (a census)
comm <- sample(as.factor(letters[1:5]), 1000, 
	prob=c(0.6,0.4,0.2,0.1,0.1), replace=TRUE)

# taking random samples from my community and calculating relative abundance
samps <- plyr::ldply(1:1000, function(x){
	set.seed(x)
	tmp <- table(sample(comm, 10))
	tmp <- tmp/sum(tmp)
	return(tmp)
})

# taking the mean of each relative abundance in the sample
colMeans(samps)


# I think I see what Andrew is saying!!!
rowMeans(samps)