Re: [Gretl-users] quickly run through ARIMA models, varying parameters, acquiring AIC, BIC, HQC?

You can use armax_auto (see time series menu in Gretl GUI). The function has a drawback: the cycle crushes on encountering a unit root in MA part of the model Also you can use auto.arima{forecast} in R My experience tells it would be better to determine the order of integration (use unit root tests) beforehand and use, say "d=1" in auto.arima (type ?auto.arima in R console) --- Оригінальне повідомлення --- Від кого: "Tim Nall" < tnall.ling(a)gmail.com > Дата: 26 квітня 2014, 03:53:32 All, Please forgive my simple questions. For ARIMA modelling, using the ACF and PACF to determine the pdq parameters requires subjective judgment based on experience. Answers are seldom clear-cut. As the subject header says, can a somewhat more objective path be found in quickly running through ARIMA models, varying parameters, acquiring AIC, BIC, HQC, and comparing? I don't think the time-series-->VAR lag selection option gets at precisely the same thing. Thank you TMN _______________________________________________ Gretl-users mailing list Gretl-users(a)lists.wfu.edu http://lists.wfu.edu/mailman/listinfo/gretl-users