betabinexch: Log posterior of logit mean and log precision for...

Description Usage Arguments Value Author(s) Examples

View source: R/betabinexch.R

Description

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

Usage

1

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)

LearnBayes documentation built on May 30, 2017, 4:48 a.m.