[R-SIG-Finance] predict.Arima question

[Rob Hyndman]

Unfortunately you can't do this using the arima() or predict() functions 
in the stats package. However, you can do what you want using the 
arima() function in the forecast package (available on CRAN). There is 
also a function best.arima() which selects the best model according to 
AIC, BIC or AICc.

Best wishes,
Rob

Felipe Santos wrote:
> Hi,
> 
> I am trying to forecast a model using predict.Arima
> 
> I found arima model for a data set: x={x1,x2,x3,...,x(t)}
> 
> arima_model = arima(x,order=c(1,0,1))
> 
> I am forecasting the next N lags using predict:
> 
> arima_pred = predict(arima_model,n.ahead = N, se.fit=T)
> 
> If I have one more point in my series, let's say x(t+1). I do not want to
> recalibrate themodel, I just want to forecast the next N-1 lags  using the
> same model for x={x1,x2,...x(t)} but without recalibrate arima.
> 
> How to do it using arima + predict.Arima ?
> 
> My problem is that I am trying to fit arima models by brute force ( trying
> lots of combinations for p and q and chosing the best model by AIC and BIC )
> I have a big time series and I am running calibration for some sub-sequence
> and I trying to forecast some points. I repeat this process for the next
> contiguous subsequence and try to forecast again, until the big series end.
> 
> Thanks
> Felipe
> 
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> 
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-- 
__________________________________________________
Professor Rob J Hyndman
Department of Econometrics & Business Statistics,
Monash University, VIC 3800, Australia
http://www.robhyndman.info/