Log posterior of logit mean and log precision for Binomial/beta exchangeable model

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Description

Computes the log posterior density of logit mean and log precision for a Binomial/beta exchangeable model

Usage

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Arguments

theta

vector of parameter values of logit eta and log K

data

a matrix with columns y (counts) and n (sample sizes)

Value

value of the log posterior

Author(s)

Jim Albert

Examples

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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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