Log posterior of logit mean and log precision for Binomial/beta exchangeable model
Computes the log posterior density of logit mean and log precision for a Binomial/beta exchangeable model
betabinexch(theta,data)
theta |
vector of parameter values of logit eta and log K |
data |
a matrix with columns y (counts) and n (sample sizes) |
value of the log posterior
Jim Albert
n=c(20,20,20,20,20) y=c(1,4,3,6,10) data=cbind(y,n) theta=c(-1,0) betabinexch(theta,data)
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