groupeddatapost: Log posterior of normal parameters when data is in grouped...
In LearnBayes: Functions for Learning Bayesian Inference

Description Usage Arguments Value Author(s) Examples

Computes the log posterior density of (M,log S) for normal sampling where the data is observed in grouped form

1	groupeddatapost(theta,data)

`theta`	vector of parameter values M and log S
`data`	list with components int.lo, a vector of left endpoints, int.hi, a vector of right endpoints, and f, a vector of bin frequencies

value of the log posterior

Jim Albert

int.lo=c(-Inf,10,15,20,25)
int.hi=c(10,15,20,25,Inf)
f=c(2,5,8,4,2)
data=list(int.lo=int.lo,int.hi=int.hi,f=f)
theta=c(20,1)
groupeddatapost(theta,data)