betabinexch {LearnBayes} | R Documentation |
Computes the log posterior density of logit mean and log precision for a Binomial/beta exchangeable model
betabinexch(theta,data)
theta |
matrix of parameter values where each row represents a value of (logit eta, log K) |
data |
a matrix with columns y (counts) and n (sample sizes) |
vector of values of the log posterior where each value corresponds to each row of the parameters in theta
Jim Albert
n=c(20,20,20,20,20) y=c(1,4,3,6,10) data=cbind(y,n) par1=c(-1,0) par2=c(-1,1) theta=rbind(par1,par2) betabinexch(theta,data)