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Implementation of the Mode Jumping Markov Chain Monte Carlo algorithm from Hubin, A., Storvik, G. (2018) <doi:10.1016/j.csda.2018.05.020>, Genetically Modified Mode Jumping Markov Chain Monte Carlo from Hubin, A., Storvik, G., & Frommlet, F. (2020) <doi:10.1214/18-BA1141>, Hubin, A., Storvik, G., & Frommlet, F. (2021) <doi:10.1613/jair.1.13047>, and Hubin, A., Heinze, G., & De Bin, R. (2023) <doi:10.3390/fractalfract7090641>, and Reversible Genetically Modified Mode Jumping Markov Chain Monte Carlo from Hubin, A., Frommlet, F., & Storvik, G. (2021) <doi:10.48550/arXiv.2110.05316>, which allow for estimating posterior model probabilities and Bayesian model averaging across a wide set of Bayesian models including linear, generalized linear, generalized linear mixed, generalized nonlinear, generalized nonlinear mixed, and logic regression models.
| Version: | 1.5.0 |
| Depends: | R (≥ 3.4.1), bigmemory |
| Imports: | glmnet, biglm, hash, BAS, stringi, parallel, methods, speedglm, stats, withr |
| Suggests: | testthat (≥ 3.0.0), bindata, clusterGeneration, reshape2 |
| Published: | 2024-05-03 |
| DOI: | 10.32614/CRAN.package.EMJMCMC |
| Author: | Aliaksandr Hubin [aut], Waldir Leoncio [cre, aut], Geir Storvik [ctb], Florian Frommlet [ctb] |
| Maintainer: | Waldir Leoncio <w.l.netto at medisin.uio.no> |
| License: | GPL-2 | GPL-3 [expanded from: GPL] |
| NeedsCompilation: | no |
| Materials: | NEWS |
| CRAN checks: | EMJMCMC results |
| Reference manual: | EMJMCMC.pdf |
| Package source: | EMJMCMC_1.5.0.tar.gz |
| Windows binaries: | r-devel: EMJMCMC_1.5.0.zip, r-release: EMJMCMC_1.5.0.zip, r-oldrel: EMJMCMC_1.5.0.zip |
| macOS binaries: | r-release (arm64): EMJMCMC_1.5.0.tgz, r-oldrel (arm64): EMJMCMC_1.5.0.tgz, r-release (x86_64): EMJMCMC_1.5.0.tgz, r-oldrel (x86_64): EMJMCMC_1.5.0.tgz |
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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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