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 |
matrix of parameter values where each row represents a value of (M, log S) |
data |
list with components b, a vector of midpoints and f, the corresponding bin frequencies |
vector of values of the log posterior where each value corresponds to each row of the parameters in theta
Jim Albert
b=c(10,15,20,25,30) f=c(2,5,8,4,2) data=list(b=b,f=f) par1=c(20,1) par2=c(22,0) theta=rbind(par1,par2) groupeddatapost(theta,data)