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aliaksah committed Apr 24, 2024
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8 changes: 3 additions & 5 deletions DESCRIPTION
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Package: EMJMCMC
Type: Package
Title: Expert Toolbox for Running (R)(G)MJMCMC for Bayesian Model Selection and Averaging
Title: Evolutionary Mode Jumping Markov Chain Monte Carlo Expert Toolbox
Version: 1.5.0
Date: 2024-04-23
Authors@R:
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person("Florian", "Frommlet", role = c("ctb"))
)
Maintainer: Waldir Leoncio <w.l.netto@medisin.uio.no>
Description: Implementation of the software from Hubin, A., Storvik, G. (2018) <doi:10.1016/j.csda.2018.05.020>, 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>, Hubin, A., Frommlet, F., & Storvik, G. (2021) <doi:10.48550/arXiv.2110.05316>, and Hubin, A., Heinze, G., & De Bin, R. (2023) <doi:10.3390/fractalfract7090641>
Description: 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 Hubin, A., Frommlet, F., & Storvik, G. (2021) <doi:10.48550/arXiv.2110.05316>.
which introduced an approach for estimating posterior model
probabilities and Bayesian model averaging and selection with possible
simultaneous feature engineering based on some primitive recursive functions.
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.
License: GPL
Depends: R (>= 3.4.1), bigmemory
Imports: glmnet, biglm, hash, BAS, stringi, parallel, methods, speedglm, stats
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