DR {BayesianTools} | R Documentation |
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.
[Package BayesianTools version 0.1.8 Index]