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FBMS (version 1.2)

Flexible Bayesian Model Selection and Model Averaging

Description

Implements the Mode Jumping Markov Chain Monte Carlo algorithm described in and its Genetically Modified counterpart described in as well as the sub-sampling versions described in for flexible Bayesian model selection and model averaging.

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Install

install.packages('FBMS')

Monthly Downloads

402

Version

1.2

License

GPL-2

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Repository

https://github.com/jonlachmann/FBMS

Maintainer

Jon Lachmann

Last Published

September 12th, 2025

Functions in FBMS (1.2)

Log likelihood function for glm regression with Zellner's g-prior and BIC-like approximations

Extract the Best Model from MJMCMC or GMJMCMC Results

logistic.loglik.ala

Log likelihood function for logistic regression with an approximate Laplace approximations used This function is created as an example of how to create an estimator that is used to calculate the marginal likelihood of a model.

Retrieve the Median Probability Model (MPM)

logistic.loglik

Log likelihood function for logistic regression with a Jeffreys parameter prior and BIC approximations of the posterior This function is created as an example of how to create an estimator that is used to calculate the marginal likelihood of a model.

Log likelihood function for glm regression with a Jeffreys parameter prior and BIC approximations of the posterior This function is created as an example of how to create an estimator that is used to calculate the marginal likelihood of a model.

Log model prior function

Log likelihood function for Gaussian regression with parameter priors from BAS package

p0p0 polynomial term

Function to plot the results, works both for results from gmjmcmc and merged results from merge.results

p0pm1 polynomial terms

p0p2 polynomial term

p0p05 polynomial term

p0p1 polynomial term

p0pm2 polynomial term

plot.mjmcmc_parallel

Plot a mjmcmc_parallel run

gaussian.loglik

Log likelihood function for gaussian regression with a Jeffreys prior and BIC approximation of MLIK with both known and unknown variance of the responses

predict.mjmcmc_parallel

Predict using a mjmcmc result object from a parallel run.

Print method for "feature" class

rmclapply: Cross-platform mclapply/forking hack for Windows

Cube root function

p3 polynomial term

gen.probs.mjmcmc

Generate a probability list for MJMCMC (Mode Jumping MCMC)

p2 polynomial term

gen.probs.gmjmcmc

Generate a probability list for GMJMCMC (Genetically Modified MJMCMC)

Main algorithm for GMJMCMC (Genetically Modified MJMCMC)

glm.logpost.bas

Log likelihood function for glm regression with parameter priors from BAS package

mjmcmc.parallel

Run multiple mjmcmc runs in parallel, merging the results before returning.

Function to generate a function string for a model consisting of features

pm2 polynomial term

Function for calculating marginal inclusion probabilities of features given a list of models

logistic.loglik.alpha

Log likelihood function for logistic regression for alpha calculation This function is just the bare likelihood function

negative ReLu function

p0p3 polynomial term

Negative GELU function

predict.bgnlm_model

Predict responses from a BGNLM model

negative heavy side function

Predict using a mjmcmc result object.

predict.gmjmcmc_parallel

Predict using a gmjmcmc result object from a parallel run.

Sigmoid function

Set the transformations option for GMJMCMC (Genetically Modified MJMCMC), this is also done when running the algorithm, but this function allows for it to be done manually.

Merge a list of multiple results from many runs This function will weight the features based on the best marginal posterior in that population and merge the results together, simplifying by merging equivalent features (having high correlation).

gmjmcmc.parallel

Run multiple gmjmcmc (Genetically Modified MJMCMC) runs in parallel returning a list of all results.

heavy side function

Square root function

Sine function for degrees

p05 polynomial term

Main algorithm for MJMCMC (Genetically Modified MJMCMC)

p0 polynomial term

pm05 polynomial term

plot.gmjmcmc_merged

Plot a gmjmcmc_merged run

summary.gmjmcmc_merged

Function to print a quick summary of the results

pm1 polynomial term

summary.gmjmcmc

Function to print a quick summary of the results

Function to plot the results, works both for results from gmjmcmc and merged results from merge.results

predict.gmjmcmc

Predict using a gmjmcmc result object.

Function to print a quick summary of the results

string.population.models

Function to get a character representation of a list of models

p0pm05 polynomial term

string.population

Function to get a character representation of a list of features

predict.gmjmcmc_merged

Predict using a merged gmjmcmc result object.

summary.mjmcmc_parallel

Function to print a quick summary of the results

Plot convergence of best/median/mean/other summary log posteriors in time

compute_effects

Compute effects for specified in labels covariates using a fitted model.

Excerpt from the Open Exoplanet Catalogue data set

tools:::Rd_package_title("FBMS")

arcsinh transform

Cosine function for degrees

Gene expression data lymphoblastoid cell lines of all 210 unrelated HapMap individuals from four populations

Physical measurements of 4177 abalones, a species of sea snail.

Breast Cancer Wisconsin (Diagnostic) Data Set

gaussian.loglik.alpha

Log likelihood function for gaussian regression for alpha calculation This function is just the bare likelihood function Note that it only gives a proportional value and is equivalent to least squares

Fit a BGNLM model using Genetically Modified Mode Jumping Markov Chain Monte Carlo (MCMC) sampling. Or Fit a BGLM model using Modified Mode Jumping Markov Chain Monte Carlo (MCMC) sampling.

Double exponential function

gaussian_tcch_log_likelihood

Log likelihood function for Gaussian regression with parameter priors from BAS package

fbms.mlik.master

Master Log Marginal Likelihood Function

gaussian.loglik.g

Log likelihood function for linear regression using Zellners g-prior

gen.params.gmjmcmc

Generate a parameter list for GMJMCMC (Genetically Modified MJMCMC)

gen.params.mjmcmc

Generate a parameter list for MJMCMC (Mode Jumping MCMC)