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Optimal Statistical Model for Forecasting Ozone

Abdollahian, M. ; Foroughi, Roya (2005)
Optimal Statistical Model for Forecasting Ozone.
IEEE International Conference on Information Technology: Coding and Computing 2005. Proceedings Vol. I.
Konferenzveröffentlichung, Bibliographie

Kurzbeschreibung (Abstract)

The objective of this paper is to apply time series analysis to Ozone data in order to obtain the optimal forecasting model . Different ARMA models are fitted to the Ozone data and the best fitted model, ARMA (20,2), is found to produce the best predictions with MAPE = 42. Applying simple exponential smoothing to the time series, however, results in even higher accuracy for predictions. This leads us to believe that in certain cases depending on the characteristics of the time series, naïve methods of forecasting may produce more accurate results.

Typ des Eintrags: Konferenzveröffentlichung
Erschienen: 2005
Autor(en): Abdollahian, M. ; Foroughi, Roya
Art des Eintrags: Bibliographie
Titel: Optimal Statistical Model for Forecasting Ozone
Sprache: Englisch
Publikationsjahr: 2005
Ort: Los Alamitos, Calif. [u.a.]
Verlag: IEEE Computer Society
Veranstaltungstitel: IEEE International Conference on Information Technology: Coding and Computing 2005. Proceedings Vol. I
Kurzbeschreibung (Abstract):

The objective of this paper is to apply time series analysis to Ozone data in order to obtain the optimal forecasting model . Different ARMA models are fitted to the Ozone data and the best fitted model, ARMA (20,2), is found to produce the best predictions with MAPE = 42. Applying simple exponential smoothing to the time series, however, results in even higher accuracy for predictions. This leads us to believe that in certain cases depending on the characteristics of the time series, naïve methods of forecasting may produce more accurate results.

Freie Schlagworte: Time series analysis, Forecasting theory, Statistics
Fachbereich(e)/-gebiet(e): 20 Fachbereich Informatik
20 Fachbereich Informatik > Graphisch-Interaktive Systeme
Hinterlegungsdatum: 16 Apr 2018 09:04
Letzte Änderung: 23 Apr 2020 07:55
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