Hello everyone,

I am experiencng some problems in producing forecasts and backcast from an
ARIMA(1,0,0) model. I need to produce an insample backcast and a seasonal
normal backcast and forecast.
I have a seasonal consumption function. By using actual data I get actual
demand. By passing Seasonal Normal regressors I need to obtain seasonal
normal demand.

I tested backcasting in arima by passing data used in the estimation back to
the model through predict. This didnt work as the output was different from
the fitted value I could see for the estimated model. In other words, in
arima I am not able to produce  my seasonal normal backcast.

I then started looking at Arima in Forecast. By passing the estimated model
to  Arima I can reproduce the fitted value from the model. My problem comes
when I try to apply that model  to different dependent (y) data, as the y is
supposed to be passed to Arima, so essentially I can do only an in sample
backcast for same dependent variable.

Is there a way I can get a Seasonal Normal backcast based on the model
estimated on actual data but by passing Seasonal Normal regressors?

Thanks,

Paolo

	[[alternative HTML version deleted]]

