Evolutionary Mode Jumping Markov Chain Monte Carlo Expert Toolbox

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Documentation for package ‘EMJMCMC’ version 1.5.0

Help Pages

do.call.emjmcmc A help function used by parall.gmj to run parallel chains of (R)(G)MJMCMC algorithms
erf erf activation function
estimate.bas.glm Obtaining Bayesian estimators of interest from a GLM model
estimate.bas.lm Obtaining Bayesian estimators of interest from a LM model
estimate.bigm Obtaining Bayesian estimators of interest from a GLM model
estimate.elnet A test function to work with elastic networks in future, be omitted so far
estimate.gamma.cpen Estimate marginal log posterior of a single BGNLM model
estimate.gamma.cpen_2 Estimate marginal log posterior of a single BGNLM model with alternative defaults
estimate.glm Obtaining Bayesian estimators of interest from a GLM model
estimate.logic.glm Obtaining Bayesian estimators of interest from a GLM model in a logic regression context
estimate.logic.lm Obtaining Bayesian estimators of interest from an LM model for the logic regression case
estimate.speedglm 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
m Product function used in the deep regression context
parall.gmj A function to run parallel chains of (R)(G)MJMCMC algorithms
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).
pinferunemjmcmc A wrapper for running the GLMM, BLR, or DBRM based inference and predictions in an expert but rather easy to use way
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
sigmoid sigmoid activation function
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)
truncfactorial Truncated factorial to avoid stack overflow for huge values