TBF Methodology Extension for Multinomial Outcomes

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Documentation for package ‘TBFmultinomial’ version 0.1.3

• DESCRIPTION file.
• User guides, package vignettes and other documentation.

Help Pages

TBFmultinomial-package	Objective Bayesian variable selection for multinomial regression and discrete time-to-event models with competing risks
AIC_BIC_based_marginalLikelihood	Marginal likelihoods based on AIC or BIC
all_formulas	Formulas of all the candidate models
as.data.frame.PMP	Convert a PMP object into a data frame
CSVS	Cause-specific variable selection (CSVS)
model_priors	Prior model probability
PIPs_by_landmarking	Posterior inclusion probabilities (PIPs) by landmarking
plot_CSVS	Plot a CSVS object
PMP	Posterior model probability
PMP-class	Class for PMP objects
postInclusionProb	Posterior inclusion probability (PIP)
sample_multinomial	Samples from a PMP object
TBF	Test-based Bayes factor
TBFmultinomial	Objective Bayesian variable selection for multinomial regression and discrete time-to-event models with competing risks
TBF_ingredients	Ingredients to calculate the TBF
VAP_data	Data on VAP acquistion in one ICU