Evolutionary Mode Jumping Markov Chain Monte Carlo Expert Toolbox R package EMJMCMC version 1.5.0 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. Software 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 Waldir Leoncio <w.l.netto@medisin.uio.no> Comprehensive R Archive Network (CRAN) Aliaksandr Hubin [aut], Waldir Leoncio [cre, aut], Geir Storvik [ctb], Florian Frommlet [ctb] GPL 2024-05-03 application/tgz https://CRAN.R-project.org/package=EMJMCMC doi:10.32614/CRAN.package.EMJMCMC