Tools for Markov Chain Monte Carlo (MCMC) simulation and performance analysis. Simulate MCMC algorithms including adaptive MCMC, evaluate their convergence rate, and compare candidate MCMC algorithms for a same target density, based on entropy and Kullback-Leibler divergence criteria. MCMC algorithms can be simulated using provided functions, or imported from external codes. This package is based upon work starting with Chauveau, D. and Vandekerkhove, P. (2013) <doi:10.1051/ps/2012004> and next articles.
| Version: | 1.0.4 |
| Depends: | R (≥ 3.0) |
| Imports: | RANN, parallel, mixtools |
| Suggests: | Rmpi, snow |
| Published: | 2019-03-08 |
| Author: | Didier Chauveau [aut, cre], Houssam Alrachid [ctb] |
| Maintainer: | Didier Chauveau <didier.chauveau at univ-orleans.fr> |
| License: | GPL (≥ 3) |
| NeedsCompilation: | yes |
| Citation: | EntropyMCMC citation info |
| In views: | Bayesian |
| CRAN checks: | EntropyMCMC results |
| Reference manual: | EntropyMCMC.pdf |
| Package source: | EntropyMCMC_1.0.4.tar.gz |
| Windows binaries: | r-devel: EntropyMCMC_1.0.4.zip, r-release: EntropyMCMC_1.0.4.zip, r-oldrel: EntropyMCMC_1.0.4.zip |
| macOS binaries: | r-release: EntropyMCMC_1.0.4.tgz, r-oldrel: EntropyMCMC_1.0.4.tgz |
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