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MCMChybridGP  

Hybrid Markov Chain Monte Carlo Using Gaussian Processes
View on CRAN: Click here


Download and install MCMChybridGP package within the R console
Install from CRAN:
install.packages("MCMChybridGP")

Install from Github:
library("remotes")
install_github("cran/MCMChybridGP")

Install by package version:
library("remotes")
install_version("MCMChybridGP", "7.0.1")



Attach the package and use:
library("MCMChybridGP")
Maintained by
Mark J. Fielding
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2026-06-24
Latest Update: 2026-06-24
Description:
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).
How to cite:
Mark J. Fielding (2026). MCMChybridGP: Hybrid Markov Chain Monte Carlo Using Gaussian Processes. R package version 7.0.1, https://cran.r-project.org/web/packages/MCMChybridGP. Accessed 14 Jul. 2026.
Previous versions and publish date:
2.1 (2009-09-22 10:22), 2.2 (2009-12-20 10:34), 3.1 (2010-09-30 09:41), 4.2 (2011-07-23 15:02), 4.3 (2011-08-12 07:55), 5.4 (2020-11-12 19:50), 7.0.1 (2026-06-24 17:10), (2026-07-09 08:09)
Other packages that cited MCMChybridGP R package
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Other R packages that MCMChybridGP depends, imports, suggests or enhances
Complete documentation for MCMChybridGP
Functions, R codes and Examples using the MCMChybridGP R package
Full MCMChybridGP package functions and examples
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