Description Usage Arguments Value Examples
Distribution of product of several discrete random variables as product X*Y
1 2 | dists.product.pair(dists, n.max = 1e+06, appr = FALSE, appr.method = 1L,
n.max.appr = 1000, r0 = 0.01, R = 1.05)
|
dists |
a list of distributions |
n.max |
maximum number of mass points of discrete distribution used in the process |
appr |
if TRUE, then the distributions are shrunken (approximated), if necessary, to not exceed n.max |
appr.method |
integer: 1 (merge mass points to lower bound); 2 (merge to upper bound) |
n.max.appr |
maximum number of mass points of shrunken distributions |
r0 |
numeric, relative tolerance used in first step of shrinking the distributions |
R |
numeric, |
list with named sublists:
cumdist1: a list with vectors x
, Fx
dist2: a list with vectors x
, fx
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 | 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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