select.IC: Selection of APFA model using penalised likelihood criteria

In gRapfa: Acyclic Probabilistic Finite Automata

Description

Selects an APFA using the algorithm described in Ankinakatte and Edwards (2014)

Usage

select.IC(dat, crit = "BIC", verbose = FALSE)

Arguments

dat	a data frame whose variables are factors. Any missing values are regarded as additional factor levels.
crit	Model selection criteria, either AIC or BIC.
verbose	If verbose=TRUE, then the function prints calculations involved in merge selection method.

Value

Returns an APFA model

Author(s)

Smitha Ankinakatte and David Edwards

References

Ankinakatte, S. and Edwards, D. Modelling discrete longitudinal data using acyclic probabilistic finite automata. Submitted to C.S.D.A.

Examples

library(gRapfa)
data(Wheeze)
G <- select.IC(Wheeze)

gRapfa documentation built on May 2, 2019, 6:54 a.m.