poissgamexch {LearnBayes} | R Documentation |
Computes the log posterior density of log alpha and log mu for a Poisson/gamma exchangeable model
poissgamexch(theta,datapar)
theta |
matrix of parameter values where each row represents a value of (log alpha, log mu) |
datapar |
list with components data, a matrix with columns e and y, and z0, prior hyperparameter |
vector of values of the log posterior where each value corresponds to each row of the parameters in theta
Jim Albert
e=c(532,584,672,722,904) y=c(0,0,2,1,1) data=cbind(e,y) par1=c(-4,0) par2=c(-4,1) z0=.5 datapar=list(data=data,z0=z0) theta=rbind(par1,par2) poissgamexch(theta,datapar)