Package: EMJMCMC 1.5.0

EMJMCMC: Evolutionary Mode Jumping Markov Chain Monte Carlo Expert Toolbox

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.

Authors:Aliaksandr Hubin [aut], Waldir Leoncio [cre, aut], Geir Storvik [ctb], Florian Frommlet [ctb]

EMJMCMC_1.5.0.tar.gz
EMJMCMC_1.5.0.zip(r-4.5)EMJMCMC_1.5.0.zip(r-4.4)EMJMCMC_1.5.0.zip(r-4.3)
EMJMCMC_1.5.0.tgz(r-4.4-any)EMJMCMC_1.5.0.tgz(r-4.3-any)
EMJMCMC_1.5.0.tar.gz(r-4.5-noble)EMJMCMC_1.5.0.tar.gz(r-4.4-noble)
EMJMCMC_1.5.0.tgz(r-4.4-emscripten)EMJMCMC_1.5.0.tgz(r-4.3-emscripten)
EMJMCMC.pdf |EMJMCMC.html✨
EMJMCMC/json (API)
NEWS

# Install 'EMJMCMC' in R:
install.packages('EMJMCMC', repos = c('https://wleoncio.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

On CRAN:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

1.46 score 29 scripts 130 downloads 19 exports 22 dependencies

Last updated 7 months agofrom:c9decd6377. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKOct 31 2024
R-4.5-winOKOct 31 2024
R-4.5-linuxOKOct 31 2024
R-4.4-winOKOct 31 2024
R-4.4-macOKOct 31 2024
R-4.3-winOKOct 31 2024
R-4.3-macOKOct 31 2024

Exports:erfestimate.bas.glmestimate.bas.lmestimate.bigmestimate.elnetestimate.gamma.cpenestimate.gamma.cpen_2estimate.glmestimate.logic.glmestimate.logic.lmestimate.speedglmLogicRegrmparall.gmjpinferunemjmcmcrunemjmcmcsigmoidsimplify.formulatruncfactorial

Dependencies:BASBHbiglmbigmemorybigmemory.sricodetoolsDBIforeachglmnethashiteratorslatticeMASSMatrixRcppRcppEigenshapespeedglmstringisurvivaluuidwithr

Readme and manuals

Help Manual

Help pageTopics
A help function used by parall.gmj to run parallel chains of (R)(G)MJMCMC algorithmsdo.call.emjmcmc
erf activation functionerf
Obtaining Bayesian estimators of interest from a GLM modelestimate.bas.glm
Obtaining Bayesian estimators of interest from a LM modelestimate.bas.lm
Obtaining Bayesian estimators of interest from a GLM modelestimate.bigm
A test function to work with elastic networks in future, be omitted so farestimate.elnet
Estimate marginal log posterior of a single BGNLM modelestimate.gamma.cpen
Estimate marginal log posterior of a single BGNLM model with alternative defaultsestimate.gamma.cpen_2
Obtaining Bayesian estimators of interest from a GLM modelestimate.glm
Obtaining Bayesian estimators of interest from a GLM model in a logic regression contextestimate.logic.glm
Obtaining Bayesian estimators of interest from an LM model for the logic regression caseestimate.logic.lm
Obtaining Bayesian estimators of interest from a GLM modelestimate.speedglm
A wrapper for running the Bayesian logic regression based inference in a easy to use wayLogicRegr
Product function used in the deep regression contextm
A function to run parallel chains of (R)(G)MJMCMC algorithmsparall.gmj
An example of user defined parallelization (cluster based) function for within an MJMCMC chain calculations (mclapply or lapply are used by default depending on specification and OS).parallelize
A wrapper for running the GLMM, BLR, or DBRM based inference and predictions in an expert but rather easy to use waypinferunemjmcmc
Mode jumping MJMCMC or Genetically Modified Mode jumping MCMC or Reversible Genetically Modified Mode jumping MCMC for variable selection, Bayesian model averaging and feature engineeringrunemjmcmc
sigmoid activation functionsigmoid
A function parsing the formula into the vectors of character arrays of responses and covariatessimplify.formula
A function that ads up posteriors for the same expression written in different character form in different parallel runs of the algorithm (mainly for Logic Regression and Deep Regression contexts)simplifyposteriors
Truncated factorial to avoid stack overflow for huge valuestruncfactorial