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MCMChybridGP: Hybrid Markov Chain Monte Carlo Using Gaussian Processes

Hybrid Markov chain Monte Carlo (MCMC) for sampling from multimodal target distributions when derivatives are unavailable. A Gaussian process approximation is used to emulate derivatives, enabling efficient exploration with parallel tempering. The method is described in Fielding, Nott and Liong (2011) <doi:10.1198/TECH.2010.09195>. The research was carried out as part of the Singapore-Delft Water Alliance Multi-Objective Multi-Reservoir Management programme (R-264-001-272).

Version: 7.0.1
Depends: R (≥ 4.2.0)
Imports: MASS, Rcpp
LinkingTo: Rcpp
Published: 2026-06-24
DOI: 10.32614/CRAN.package.MCMChybridGP
Author: Mark J. Fielding [aut, cre]
Maintainer: Mark J. Fielding <mark.fielding at gmx.com>
License: GPL-2
NeedsCompilation: yes
CRAN checks: MCMChybridGP results

Documentation:

Reference manual: MCMChybridGP.html , MCMChybridGP.pdf

Downloads:

Package source: MCMChybridGP_7.0.1.tar.gz
Windows binaries: r-devel: not available, r-release: MCMChybridGP_7.0.1.zip, r-oldrel: not available
macOS binaries: r-release (arm64): MCMChybridGP_7.0.1.tgz, r-oldrel (arm64): MCMChybridGP_7.0.1.tgz, r-release (x86_64): MCMChybridGP_7.0.1.tgz, r-oldrel (x86_64): MCMChybridGP_7.0.1.tgz
Old sources: MCMChybridGP archive

Linking:

Please use the canonical form https://CRAN.R-project.org/package=MCMChybridGP to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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