Dakota Reference Manual: delayed_rejection

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delayed_rejection

Use the Delayed Rejection MCMC algorithm

## Topics

This keyword is related to the topics:

- bayesian_calibration

## Specification

Alias: none

Argument(s): none

Default: dram

## Description

This keyword specifies the use of the Delayed Rejection algorithm in which there can be a delay in rejecting samples from the chain. That is, the "DR" part of DRAM is used but the "AM" part is not, rather a regular Metropolis-Hastings algorithm is used.

Default Behavior

Five MCMC algorithm variants are supported: `dram`, `delayed_rejection`, `adaptive_metropolis`, `metropolis_hastings`, and `multilevel`. The default is `dram`.

Usage Tips

If the user knows something about the proposal covariance or the proposal covariance is informed through derivative information, using `delayed_rejection` is preferred over `dram:` the proposal covariance is already being informed by derivative information and the adaptive metropolis is not necessary.

## Examples

    method,
            bayes_calibration queso
              delayed_rejection
              samples = 10000 seed = 348

## See Also

These keywords may also be of interest:

- proposal_covariance