This function calculates the ingredients needed to compute the TBFs: like the deviances with their degrees of freedom of the relevant candidate models.
TBF_ingredients(fullModel = NULL, data, discreteSurv = FALSE,
numberCores = 1, candidateModels = NULL, package = "nnet",
maxit = 150)formula of the model including all potential variables
the data frame with all the information
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.
How many cores should be used in parallel?
Instead of defining the full model we can also specify the candidate models whose deviance statistic and d.o.f should be computed
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'
Only needs to be specified with package nnet: maximal
number of iterations
an object of class TBF.ingredients