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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