You also may want to look at auto.arima in the 'forecast' package,
which will return the "best" ARIMA model based on AIC/AICc/BIC values
?auto.arima
hth
c
On 09/05/2010 06:02 PM, Stephan Kolassa wrote:
Hi,
basically, you know 5 periods later. If you use a good error measure,
that is.
I am a big believer in AIC for model selection. I believe that arima()
also gives you the AIC of a fitted model, or try AIC(arima1).
Other ideas include keeping a holdout sample or some such.
I'd recommend looking at a time series textbook.
HTH,
Stephan
Am 05.09.2010 22:37, schrieb lord12:
How do you evaluate the predictive models? For example if I have:
arima1 = arima(training, order = c(1,1,1))
arima2 = arima(training, order = c(0,0,0))
x.fore = predict(arima1, n.ahead=5)
x.fore1 = predict(arima2, n.ahead = 5)
How do I know which arima model is better for prediction?
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