Likelihood object for Binomial error distribution
Creates a likelihood object for ash for use with Binomial error distribution
lik_binom(y, n, link = c("identity", "logit"))y |
Binomial observations |
n |
Binomial number of trials |
link |
Link function. The "identity" link directly puts unimodal prior on Binomial success probabilities p, and "logit" link puts unimodal prior on logit(p). |
Suppose we have Binomial observations y where y_i\sim Bin(n_i,p_i).
We either put an unimodal prior g on the success probabilities p_i\sim g (by specifying
link="identity") or on the logit success probabilities logit(p_i)\sim g
(by specifying link="logit"). Either way, ASH with this Binomial likelihood function
will compute the posterior mean of the success probabilities p_i.
p = rbeta(100,2,2) # prior mode: 0.5 n = rpois(100,10) y = rbinom(100,n,p) # simulate Binomial observations ash(rep(0,length(y)),1,lik=lik_binom(y,n))
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