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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).

Versions across snapshots

VersionRepositoryFileSize
7.0.1 rolling linux/jammy R-4.5 MCMChybridGP_7.0.1.tar.gz 130.8 KiB
7.0.1 rolling linux/noble R-4.5 MCMChybridGP_7.0.1.tar.gz 131.6 KiB
7.0.1 rolling source/ R- MCMChybridGP_7.0.1.tar.gz 18.1 KiB
7.0.1 latest linux/jammy R-4.5 MCMChybridGP_7.0.1.tar.gz 130.8 KiB
7.0.1 latest linux/noble R-4.5 MCMChybridGP_7.0.1.tar.gz 131.6 KiB
7.0.1 latest source/ R- MCMChybridGP_7.0.1.tar.gz 18.1 KiB
7.0.1 2026-04-23 source/ R- MCMChybridGP_7.0.1.tar.gz 0 B

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