"Milos Milenkovic" <firstname.lastname@example.org> wrote in message <email@example.com>... > Dear, > parameter estimation in ARIMA are performed on adjusted time series (first, seasonal differencing) or original nonstationary time series? > Best, > Milos
If I understand you correctly, the parameters of an ARIMA model are estimated using the original, non-stationary series.
To clarify, I mean that the data is not explicitly differenced to remove any seasonal and non-seasonal integration effects, and then that differenced data then fit to an ARMA model. For example, suppose you want to estimate an ARIMA(P,1,Q) model. We do not fit an ARMA(P,Q) model to the first difference of the original, non-stationary data.
In other words, whatever differencing is required is performed by the underlying lag operator polynomials applied directly to the non-stationary data ? the lag operator polynomials do the work.