Flexible Bayesian Model Selection and Model Averaging

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Documentation for package ‘FBMS’ version 1.0

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FBMS-package Flexible Bayesian Model Selection and Model Averaging
breastcancer Breast Cancer Wisconsin (Diagnostic) Data Set
compute_effects Compute effects for specified in labels covariates using a fitted model.
cos_deg Cosine function for degrees
diagn_plot Plot convergence of best/median/mean/other summary log posteriors in time
erf erf function
exoplanet Excerpt from the Open Exoplanet Catalogue data set
exp_dbl Double exponential function
FBMS Flexible Bayesian Model Selection and Model Averaging
fbms 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.
gauss Gaussian function
gaussian.loglik Log likelihood function for gaussian regression with a prior p(m)=r*sum(total_width).
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
gelu GELU function
gen.params.gmjmcmc Generate a parameter list for GMJMCMC (Genetically Modified MJMCMC)
gen.params.mjmcmc Generate a parameter list for MJMCMC (Mode Jumping MCMC)
gen.probs.gmjmcmc Generate a probability list for GMJMCMC (Genetically Modified MJMCMC)
gen.probs.mjmcmc Generate a probability list for MJMCMC (Mode Jumping MCMC)
gmjmcmc Main algorithm for GMJMCMC (Genetically Modified MJMCMC)
gmjmcmc.parallel Run multiple gmjmcmc (Genetically Modified MJMCMC) runs in parallel returning a list of all results.
hs heavy side function
linear.g.prior.loglik Log likelihood function for linear regression using Zellners g-prior
logistic.loglik Log likelihood function for logistic regression with a prior p(m)=sum(total_width) This function is created as an example of how to create an estimator that is used to calculate the marginal likelihood of a model.
logistic.loglik.alpha Log likelihood function for logistic regression for alpha calculation This function is just the bare likelihood function
marginal.probs Function for calculating marginal inclusion probabilities of features given a list of models
merge_results Merge a list of multiple results from many runs This function will weight the features based on the best mlik in that population and merge the results together, simplifying by merging equivalent features (having high correlation).
mjmcmc Main algorithm for MJMCMC (Genetically Modified MJMCMC)
mjmcmc.parallel Run multiple mjmcmc runs in parallel, merging the results before returning.
model.string Function to generate a function string for a model consisting of features
ngelu Negative GELU function
nhs negative heavy side function
not not x
nrelu negative ReLu function
p0 p0 polynomial term
p05 p05 polynomial term
p0p0 p0p0 polynomial term
p0p05 p0p05 polynomial term
p0p1 p0p1 polynomial term
p0p2 p0p2 polynomial term
p0p3 p0p3 polynomial term
p0pm05 p0pm05 polynomial term
p0pm1 p0pm1 polynomial terms
p0pm2 p0pm2 polynomial term
p2 p2 polynomial term
p3 p3 polynomial term
plot.gmjmcmc Function to plot the results, works both for results from gmjmcmc and merged results from merge.results
plot.gmjmcmc_merged Plot a gmjmcmc_merged run
plot.mjmcmc Function to plot the results, works both for results from gmjmcmc and merged results from merge.results
plot.mjmcmc_parallel Plot a mjmcmc_parallel run
pm05 pm05 polynomial term
pm1 pm1 polynomial term
pm2 pm2 polynomial term
predict.gmjmcmc Predict using a gmjmcmc result object.
predict.gmjmcmc_merged Predict using a merged gmjmcmc result object.
predict.gmjmcmc_parallel Predict using a gmjmcmc result object from a parallel run.
predict.mjmcmc Predict using a mjmcmc result object.
predict.mjmcmc_parallel Predict using a mjmcmc result object from a parallel run.
print.feature Print method for "feature" class
relu ReLu function
set.transforms 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.
sigmoid Sigmoid function
sin_deg Sine function for degrees
sqroot Square root function
string.population Function to get a character respresentation of a list of features
string.population.models Function to get a character respresentation of a list of models
summary.gmjmcmc Function to print a quick summary of the results
summary.gmjmcmc_merged Function to print a quick summary of the results
summary.mjmcmc Function to print a quick summary of the results
summary.mjmcmc_parallel Function to print a quick summary of the results
to23 To the 2.3 power function
to25 To 2.5 power
to35 To 3.5 power
to72 To the 7/2 power function
troot Cube root function