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.

startValue

iterations

minimum values for the parameter vector or NULL if FUN is of class BayesianSetup

parmin

maximum values for the parameter vector or NULL if FUN is of class BayesianSetup

parmax

function to be sampled from or object of class bayesianSetup

The Delayed Rejection Algorithm (Tierney and Mira, 1999)

General-purpose MCMC and SMC samplers, as well as plot and diagnostic functions for Bayesian statistics, with a particular focus on calibrating complex system models. Implemented samplers include various Metropolis MCMC variants (including adaptive and/or delayed rejection MH), the T-walk, two differential evolution MCMCs, two DREAM MCMCs, and a sequential Monte Carlo (SMC) particle filter.

DR: The Delayed Rejection Algorithm

Description

Usage

Arguments

References