join_unobserved: Join situations with no observations

View source: R/4-model-selection.R

join_unobservedR Documentation

Join situations with no observations

Description

Join situations with no observations

Usage

join_unobserved(
  object,
  fit = TRUE,
  trace = 0,
  name = "UNOBSERVED",
  scope = sevt_varnames(object)[-1],
  lambda = object$lambda
)

Arguments

object

an object of class sevt with associated data.

fit

if TRUE update model's probabilities.

trace

if > 0 print information to console.

name

character, name for the new stage storing unobserved situations.

scope

character vector, list of variables in object.

lambda

smoothing parameter for the fitting.

Details

It takes as input a (fitted) staged event tree object and it joins, in the same stage, all the situations with zero recorded observations. Since such joining does not change the log-likelihood of the model, it is a useful (time-wise) pre-processing prior to others model selection algorithms.

Unobserved situations can be joined directly in full or indep, by setting join_unobserved = TRUE.

Value

a staged event tree with at most one stage per variable with no observations. If, as default, fit=TRUE the model will be re-fitted, if fit=FALSE probabilities in the output model are not estimated.

Examples

DD <- generate_xor_dataset(n = 5, N = 10)
model_full <- full(DD, lambda = 1, join_unobserved = FALSE)
model <- join_unobserved(model_full)
logLik(model_full)
logLik(model)
BIC(model_full, model)

stagedtrees documentation built on April 29, 2022, 1:06 a.m.