TBF {TBFmultinomial}

Test-based Bayes factor

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