loglikelihood_proportions: The (incomplete data) loglikelihood function for the...

In johannabertl/SelectionMix: Negative binomial mixture model

Description

The parameters alpha and beta are known.

Usage

loglikelihood_proportions(theta, x.non, alpha, beta, cvec)

Arguments

theta	c(p1, p2, ..., pk-1)
x.non	vector of non-synonymous mutation count
cvec	vector of k positive values c(c1, ..., ck)

Author(s)

Johanna Bertl

Examples

c1 = 0.5; c2 = 10
p1 = 0.2; p2 = 0.8
alpha = 10
beta = 5

mutations = rnegbinmix(n=3000, alpha=alpha, beta=beta, c=c(c1, c2), p = c(p1, p2))

# likelihood surface

p1vec = seq(0.11, 0.3, by=0.01)

llp1 = numeric(20)

for(i in 1:20){
 llp1[i] = loglikelihood_proportions(theta=p1vec[i], x.non = mutations, alpha = alpha, beta = beta, cvec=c(c1, c2))
}

plot(p1vec, llp1, t="b")
abline(v=p1, col="red")

johannabertl/SelectionMix documentation built on May 3, 2019, 4:03 p.m.