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,...)
Arguments
logpost |
function that defines the logarithm of the posterior density |
mode |
vector that is a guess at the posterior mode |
... |
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 2.15.1 Index]