data(freqsNLngm)
set.seed(123)
x <- sample.profiles(1,freqsNLngm)
# per locus distribution of kinship index
dists <- ki.dist(x,hyp.1="FS",hyp.2="UN",hyp.true="UN")
n <- sapply(dists,function(x) length(x$fx))
prod(n) # too many outcomes to store!
# but, for two subsets of the loci, the distribution can be obtained
pair <- dists.product.pair(dists)
str(pair) # with these, we can compute exceedance probabilities quickly
# obtain the cdf as a function
cdf <- dist.pair.cdf(pair)
cdf(1)
# plot the cdf
x0 <- seq(from=-10,to=5,length=50)
plot(x0,cdf(10^x0),type="l",xlab="x",ylab="Fn(x)")
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