MCMChybridGP (version 5.4)
Hybrid Markov Chain Monte Carlo using Gaussian Processes
Description
Hybrid Markov chain Monte Carlo (MCMC) to simulate from a
multimodal target distribution. A Gaussian process
approximation makes this possible when derivatives are unknown.
The Package serves to minimize the number of function
evaluations in Bayesian calibration of computer models using
parallel tempering. It allows replacement of the true target
distribution in high temperature chains, or complete replacement
of the target. Methods used are described in, "Efficient MCMC
schemes for computationally expensive posterior distributions",
Fielding et al. (2011) .
The research presented in this work was carried out as part of
the Singapore-Delft Water Alliance Multi-Objective
Multi-Reservoir Management research programme (R-264-001-272).