DR: The Delayed Rejection Algorithm

In BayesianTools: General-Purpose MCMC and SMC Samplers and Tools for Bayesian Statistics

The Delayed Rejection Algorithm

Description

The Delayed Rejection Algorithm (Tierney and Mira, 1999)

Usage

DR(
  startValue = NULL,
  iterations = 10000,
  nBI = 0,
  parmin = NULL,
  parmax = NULL,
  f1 = 1,
  f2 = 0.5,
  FUN
)

Arguments

startValue	vector with the start values for the algorithm. Can be NULL if FUN is of class BayesianSetup. In this case startValues are sampled from the prior.
iterations	iterations to run
nBI	number of burnin
parmin	minimum values for the parameter vector or NULL if FUN is of class BayesianSetup
parmax	maximum values for the parameter vector or NULL if FUN is of class BayesianSetup
f1	scaling factor for first proposal
f2	scaling factor for second proposal
FUN	function to be sampled from or object of class bayesianSetup

Author(s)

Francesco Minunno

References

Tierney, Luke, and Antonietta Mira. "Some adaptive Monte Carlo methods for Bayesian inference." Statistics in medicine 18.1718 (1999): 2507-2515.

BayesianTools documentation built on Feb. 16, 2023, 8:44 p.m.