I am a beginner in the whole forecasting/regression/time-series topic. While reading "Forecasting: principles and practice" from Rob J Hyndman and George Athanasopoulos i found something strange.
library(fpp)
test <- tslm(ausbeer ~ trend+season)
#summary(test)
#plot(ausbeer, col='grey')
#lines(fitted(test), col='red')
AIC(test)
> 2327.316
CV(test)
CV AIC AICc BIC AdjR2
3582.0767318 1728.5234412 1728.9352059 1748.6345900 0.5377408
Why is there a difference in the AIC values (Akaike's Information Criterion)? As far as i understood AIC(test)
and the AIC value in the CV(test)
should be the same.
extractAIC()
(used byCV()
) which leaves out a constant term, andAIC()
, which appears to give a computation consistent with the full Normal log-likelihood expression. $\endgroup$ – Ben Bolker Sep 5 '15 at 3:10