UComp (version 4.0.1)

AIC.UComp: AIC.UComp

Description

Extract AIC value of UComp object

Usage

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

Arguments

object

Object of class “UComp”.

...

Additional inputs to function.

k

The penalty per parameter to be used.

Author

Diego J. Pedregal

Details

Selection criteria for models with different number of parameters, the smaller AIC the better. The formula used here is \(AIC=-2 (ln(L) - k) / n\), where \(ln(L)\) is the log-likelihood at the optimum, \(k\) is the number of parameters plus non-stationary states and \(n\) is the number of observations. Mind that this formulation differs from the usual definition that does not divide by \(n\). This makes that AIC(m) and AIC(logLik(m)) give different results, being m an UComp object.

See Also

UC, UCmodel, UCvalidate, UCfilter, UCsmooth, UCdisturb, UCcomponents

Examples

if (FALSE) {
y <- log(AirPassengers)
m1 <- UCmodel(y, model = "llt/equal/arma(0,0)")
AIC(m1)
}