laplace {LearnBayes}R Documentation

Summarization of a posterior density by the Laplace method

Description

For a general posterior density, computes the posterior mode, the associated variance-covariance matrix, and an estimate at the logarithm at the normalizing constant.

Usage

laplace(logpost,mode,iter,par)

Arguments

logpost function that defines the logarithm of the posterior density
mode vector that is a guess at the posterior mode
iter number of iterations of Newton-Raphson algorithm
par vector or list of parameters associated with the function logpost

Value

mode current estimate at the posterior mode
var current estimate at the associated variance-covariance matrix
int estimate at the logarithm of the normalizing constant

Author(s)

Jim Albert

Examples

logpost=function(theta,data)
{
s=5
val=0*theta
for (i in 1:length(data))
{
val=val-log(1+(data[i]-theta)^2/s^2)
}
return(val)
}
data=c(10,12,14,13,12,15)
laplace(logpost,10,5,data)

[Package LearnBayes version 1.0 Index]