R: Summarization of a posterior density by the Laplace method

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 Index]