gmnl (version 1.1-3.2)

AIC.gmnl: Akaike's Information Criterion

Description

Calculate the Akaike's information Criterion (AIC) or the Bayesian information Criterion (BIC) for an object of class gmnl.

Usage

# S3 method for gmnl
AIC(object, ..., k = 2)
# S3 method for gmnl
BIC(object, ...)

Arguments

object

a fitted model of class gmnl.

...

additional arguments to be passed to or from other functions.

k

a numeric value, use as penalty coefficient for number of parameters in the fitted model.

Value

A numeric value with the corresponding AIC or BIC value.

Details

For more information see AIC or BIC

See Also

gmnl for the estimation of multinomial logit models with observed and unobserved individual heterogeneity.

Examples

# NOT RUN {
## Estimate MNL model
data("TravelMode", package = "AER")
library(mlogit)
TM <- mlogit.data(TravelMode, choice = "choice", shape = "long", 
                 alt.levels = c("air", "train", "bus", "car"), chid.var = "individual")
                 
mnl <- gmnl(choice ~ wait + vcost + travel + gcost | 0 , data = TM)
AIC(mnl)
BIC(mnl)
# }