Good morning to you all,
Sorry for taking your time from your research and
teaching schedules.
If you have a non-stationary univariate time Series
data that has the transformation:
Say; l.dat-log (series)
d.ldat-diff (l.dat, differences=1)
and you fit say arima model.
predit.arima-predict
If you just want point forecasts, it's simple:
Let your original series be X_t, t=1, ..., N.
Let Y_t = log(X_t).
Let Z_t = Y_t - Y_{t-1}, t = 2, ..., N.
Fit your model and forecast, obtaining Z-hat__1, ..., Z-hat_10.
Then Y-hat_{N+1} = Y_N + Z-hat_1, Y-hat_{N+2} = Y-hat_{N+1} + Z-hat_2,
.,
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