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Akaike information criterion

Usage

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

Arguments

object

an object of the class bellreg.

...

further arguments passed to or from other methods.

k

numeric, the penalty per parameter to be used; the default k = 2 is the classical AIC.

Value

the Akaike information criterion value when a single model is passed to the function; otherwise, a data.frame with the Akaike information criterion values and the number of parameters is returned.

Examples

# \donttest{
library(bellreg)
data(faults)
fit1 <- bellreg(nf ~ 1, data = faults, approach = "mle")
fit2 <- bellreg(nf ~ lroll, data = faults, approach = "mle")
AIC(fit1, fit2)
#>    fit      aic npars
#> 1 fit2 181.9228     2
#> 2 fit1 195.5679     1
# }