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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 |
| Reference manual: | MCMChybridGP.html , MCMChybridGP.pdf |
| 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 |
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