groupeddatapost {LearnBayes} | R Documentation |
Computes the log posterior density of (M,log S) for normal sampling where the data is observed in grouped form
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)