logpoissnormal: Log posterior with Poisson sampling and normal prior

In LearnBayes: Functions for Learning Bayesian Inference

Description

Computes the logarithm of the posterior density of a Poisson log mean with a normal prior

Usage

logpoissnormal(theta,datapar)

Arguments

theta	vector of values of the log mean parameter
datapar	list with components data, vector of observations, and par, vector of parameters of the normal prior

Value

vector of values of the log posterior for all values in theta

Author(s)

Jim Albert

Examples

data=c(2,4,3,6,1,0,4,3,10,2)
par=c(0,1)
datapar=list(data=data,par=par)
theta=c(-1,0,1,2)
logpoissnormal(theta,datapar)

LearnBayes documentation built on May 1, 2019, 7:03 p.m.