TBF: Test-based Bayes factor

In TBFmultinomial: TBF Methodology Extension for Multinomial Outcomes

Description

This function computes the TBF as well as g

Usage

TBF(ingredients = NULL, fullModel = NULL, method = "LEB", data = NULL,
  discreteSurv = TRUE, prior = NULL, package = "nnet", maxit = 150)

Arguments

ingredients	TBF_ingredients_object ingredients for the TBF (and g) calculation.
fullModel	if ingredients is NULL, formula of the model including all potential variables
method	tells us which method for the definition of g should be used. Possibilities are: LEB, GEB, g=n, hyperG, ZS, ZSadapted and hyperGN
data	the data frame with all the information. Only needed if ingredients is NULL
discreteSurv	Boolean variable telling us whether a 'simple' multinomial regression is looked for or if the goal is a discrete survival-time model for multiple modes of failure is needed.
prior	should a dependent or a flat prior be used on the model space? Only needed if method = `GEB`.
package	Which package should be used to fit the models; by default the nnet package is used; we could also specify to use the package 'VGAM'
maxit	Only needs to be specified with package nnet: maximal number of iterations

Value

A list with the TBF and the g (if it is fixed) for all the candidate models.

Author(s)

Rachel Heyard

TBFmultinomial documentation built on May 2, 2019, 2:11 p.m.