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Title: Automatic ARIMA modeling using RcmdrPlugin.SPSS Authors:  Dedi Rosadi - Universitas Gadjah Mada (Indonesia) [presenting]
Abstract: In some application of time series modeling, it is necessary to obtain forecast of various types of data automatically and possibly, in real-time way, for instance, to do a real-time processing of the satellite data. Various automatic algorithms for modeling ARIMA models are available in the literature, where we will discuss two methods in particular. One of the method is based on a combination between the best exponential smoothing model to obtain the forecast, together with state-space approach of the underlying model to obtain the prediction interval. Other method, which is more advanced method, is based on X-13-ARIMA-SEATS, the seasonal adjustment software by the US Census Bureau. These approaches are implemented in our R-GUI package RcmdrPlugin.Econometrics which now already integrated in our new and more comprehensive R-GUI package RcmdrPlugin.SPSS. We provide application of the methods and the tool using real data.