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,par)

Arguments

logpost function that defines the logarithm of the posterior density
mode vector that is a guess at the posterior mode
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
converge indication (TRUE or FALSE) if the algorithm converged

Author(s)

Jim Albert

Examples

logpost=function(theta,data)
{
s=5
sum(-log(1+(data-theta)^2/s^2))
}
data=c(10,12,14,13,12,15)
start=10
laplace(logpost,start,data)

[Package LearnBayes version 2.0 Index]