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EMJMCMC (version 1.5.0)

Evolutionary Mode Jumping Markov Chain Monte Carlo Expert Toolbox

Description

Implementation of the Mode Jumping Markov Chain Monte Carlo algorithm from Hubin, A., Storvik, G. (2018) , Genetically Modified Mode Jumping Markov Chain Monte Carlo from Hubin, A., Storvik, G., & Frommlet, F. (2020) , Hubin, A., Storvik, G., & Frommlet, F. (2021) , and Hubin, A., Heinze, G., & De Bin, R. (2023) , and Reversible Genetically Modified Mode Jumping Markov Chain Monte Carlo from Hubin, A., Frommlet, F., & Storvik, G. (2021) , 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.

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Version

Install

install.packages('EMJMCMC')

Monthly Downloads

150

Version

1.5.0

License

GPL

Maintainer

Waldir Leoncio

Last Published

May 3rd, 2024

Functions in EMJMCMC (1.5.0)

pinferunemjmcmc

A wrapper for running the GLMM, BLR, or DBRM based inference and predictions in an expert but rather easy to use way
estimate.logic.glm

Obtaining Bayesian estimators of interest from a GLM model in a logic regression context
parallelize

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).
parall.gmj

A function to run parallel chains of (R)(G)MJMCMC algorithms
estimate.speedglm

Obtaining Bayesian estimators of interest from a GLM model
sigmoid

sigmoid activation function
m

Product function used in the deep regression context
simplify.formula

A function parsing the formula into the vectors of character arrays of responses and covariates
simplifyposteriors

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)
estimate.logic.lm

Obtaining Bayesian estimators of interest from an LM model for the logic regression case
truncfactorial

Truncated factorial to avoid stack overflow for huge values
runemjmcmc

Mode jumping MJMCMC or Genetically Modified Mode jumping MCMC or Reversible Genetically Modified Mode jumping MCMC for variable selection, Bayesian model averaging and feature engineering
estimate.bigm

Obtaining Bayesian estimators of interest from a GLM model
estimate.gamma.cpen_2

Estimate marginal log posterior of a single BGNLM model with alternative defaults
estimate.gamma.cpen

Estimate marginal log posterior of a single BGNLM model
estimate.bas.lm

Obtaining Bayesian estimators of interest from a LM model
estimate.elnet

A test function to work with elastic networks in future, be omitted so far
erf

erf activation function
estimate.glm

Obtaining Bayesian estimators of interest from a GLM model
LogicRegr

A wrapper for running the Bayesian logic regression based inference in a easy to use way
estimate.bas.glm

Obtaining Bayesian estimators of interest from a GLM model
do.call.emjmcmc

A help function used by parall.gmj to run parallel chains of (R)(G)MJMCMC algorithms