R: Posterior Mode from an MCMC Sample

postmode {extRemes} | R Documentation

## Posterior Mode from an MCMC Sample

### Description

Calculate the posterior mode from an MCMC sample for “fevd” objects.

### Usage

    postmode(x, burn.in = 499, verbose = FALSE, ...)

    ## S3 method for class 'fevd'
    postmode(x, burn.in = 499, verbose = FALSE, ...)

### Arguments

`x` | An object of class “fevd” where component `method` = “Bayesian”.
`burn.in` | The furst burn.in samples from the posterior distribution will be removed before calculation.
`verbose` | logical, should progress information be printed to the screen.
`...` | Not used.

### Details

The log-likelihood and (log) prior is calculated for every sample from the chain, and added together, giving `h`. The parameters from the sample that yield the maximum value for `h` are returned. If more than one set of parameters yield a maximum, their average is returned.

### Value

A named numeric vector is returned giving the paramter values.

### Author(s)

Eric Gilleland

### See Also

`fevd`, `findpars`

### Examples

    data(ftcanmax)

    fit <- fevd(Prec, ftcanmax, method="Bayesian", iter = 1000, verbose=TRUE)

    postmode(fit)

[Package extRemes version 2.0-12 Index]