FBMS1.3 package

Flexible Bayesian Model Selection and Model Averaging

aggr.fbms_predict

Access Aggregated Predictions

aggr

Generic for Accessing Aggregated Predictions

arcsinh

Arcsinh Transform

coef.bgnlm_model

Coefficients for BGNLM Model

coef.gmjmcmc_merged

Coefficients for GMJMCMC Merged Model

coef.gmjmcmc

Coefficients for GMJMCMC Model

coef.mjmcmc_parallel

Coefficients for MJMCMC Parallel Model

coef.mjmcmc

Coefficients for MJMCMC Model

compute_effects

Compute Effects for Specified Covariates Using a Fitted Model

cos_deg

Cosine Function for Degrees

diagn_plot

Plot Convergence Diagnostics for GMJMCMC or GMJMCMC Merged Results

erf

Erf Function

exp_dbl

Double Exponential Function

FBMS-package

tools:::Rd_package_title("FBMS")

fbms.mlik.master

Master Log Marginal Likelihood Function

fbms

Fit a BGNLM Model Using MJMCMC or GMJMCMC Sampling.

fitted.fbms_predict

Access Fitted Values

gaussian.loglik

Log Likelihood Function for Gaussian Regression with a Jeffreys Prior ...

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)

get.best.model

Extract the Best Model from MJMCMC or GMJMCMC Results

get.mpm.model

Retrieve the Median Probability Model (MPM)

gmjmcmc.parallel

Run Multiple GMJMCMC (Genetically Modified MJMCMC) Runs in Parallel.

gmjmcmc

Main Algorithm for GMJMCMC (Genetically Modified MJMCMC)

hs

Heavy Side Function

impute_x_pred

Impute Missing Values in Test Data Using Training Data

impute_x

Impute Missing Values in the Data

log_prior

Log Model Prior Function

logistic.loglik

Log Likelihood Function for Logistic Regression with a Jeffreys Parame...

marginal.probs

Function for Calculating Marginal Inclusion Probabilities of Features ...

merge_results

Merge a List of Multiple Results from Many Runs

mjmcmc.parallel

Run Multiple MJMCMC Runs in Parallel, Merging the Results Before Retur...

mjmcmc

Main Algorithm for MJMCMC (Genetically Modified MJMCMC)

model.string

Function to Generate a Function String for a Model Consisting of Featu...

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.bgnlm_model

Plot BGNLM Model

plot.fbms_predict

Plot FBMS Prediction Object

plot.gmjmcmc_merged

Plot a gmjmcmc_merged Run

plot.gmjmcmc

Function to Plot GMJMCMC Results and Merged Results from merge.results

plot.mjmcmc_parallel

Plot an mjmcmc_parallel Run

plot.mjmcmc

Function to Plot GMJMCMC Results and Merged Results from merge.results

pm05

pm05 Polynomial Term

pm1

pm1 Polynomial Term

pm2

pm2 Polynomial Term

predict.bgnlm_model

Predict Responses from a BGNLM Model

predict.gmjmcmc_merged

Predict Using a Merged GMJMCMC Result Object

predict.gmjmcmc_parallel

Predict Using a GMJMCMC Result Object from a Parallel Run

predict.gmjmcmc

Predict Using a GMJMCMC Result Object

predict.mjmcmc_parallel

Predict Using an MJMCMC Result Object from a Parallel Run

predict.mjmcmc

Predict Using an MJMCMC Result Object

predmean.fbms_predict

Access Mean Predictions

predmean

Generic for Accessing Mean Predictions

predquantiles.fbms_predict

Access Quantile Predictions

predquantiles

Generic for Accessing Quantile Predictions

print.bgnlm_model

Print BGNLM Model Object

print.fbms_predict

Print FBMS Prediction Object

print.feature

Print Method for "feature" Class

print.gmjmcmc_merged

Print GMJMCMC Merged Model Object

print.gmjmcmc

Print GMJMCMC Model Object

print.mjmcmc_parallel

Print MJMCMC Parallel Model Object

print.mjmcmc

Print MJMCMC Model Object

relu

ReLU Function

residuals.bgnlm_model

Residuals for BGNLM Model

residuals.gmjmcmc_merged

Residuals for GMJMCMC Merged Model

residuals.gmjmcmc

Residuals for GMJMCMC Model

residuals.mjmcmc_parallel

Residuals for MJMCMC Parallel Model

residuals.mjmcmc

Residuals for MJMCMC Model

rmclapply

rmclapply: Cross-Platform mclapply/Forking Hack for Windows

set.transforms

Set the Transformations Option for GMJMCMC (Genetically Modified MJMCM...

sigmoid

Sigmoid Function

sin_deg

Sine Function for Degrees

sqroot

Square Root Function

string.population.models

Function to Get a Character Representation of a List of Models

string.population

Function to Get a Character Representation of a List of Features

summary.fbms_predict

Summary of FBMS Prediction Object

summary.gmjmcmc_merged

Function to Print a Quick Summary of the Results

summary.gmjmcmc

Function to Print a Quick Summary of the Results

summary.mjmcmc_parallel

Function to Print a Quick Summary of the Results

summary.mjmcmc

Function to Print a Quick Summary of the Results

troot

Cube Root Function

Implements the Mode Jumping Markov Chain Monte Carlo algorithm described in <doi:10.1016/j.csda.2018.05.020> and its Genetically Modified counterpart described in <doi:10.1613/jair.1.13047> as well as the sub-sampling versions described in <doi:10.1016/j.ijar.2022.08.018> for flexible Bayesian model selection and model averaging.