Modeling Data Containing Outliers using ARIMA Additive Outlier (ARIMA-AO)

The aim this study is discussed on the detection and correction of data containing the additive outlier (AO) on the model ARIMA (p, d, q). The process of detection and correction of data using an iterative procedure popularized by Box, Jenkins, and Reinsel (1994). By using this method we obtained an...

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Veröffentlicht in:	Journal of physics. Conference series 2018-01, Vol.954 (1), p.12010
Hauptverfasser:	Ahmar, Ansari Saleh, Guritno, Suryo, Abdurakhman, Rahman, Abdul, Awi, Alimuddin, Minggi, Ilham, Tiro, M Arif, Aidid, M Kasim, Annas, Suwardi, Sutiksno, Dian Utami, Ahmar, Dewi S, Ahmar, Kurniawan H, Ahmar, A Abqary, Zaki, Ahmad, Abdullah, Dahlan, Rahim, Robbi, Nurdiyanto, Heri, Hidayat, Rahmat, Napitupulu, Darmawan, Simarmata, Janner, Kurniasih, Nuning, Abdillah, Leon Andretti, Pranolo, Andri, Haviluddin, Albra, Wahyudin, Arifin, A Nurani M
Format:	Artikel
Sprache:	eng
Schlagworte:	Autoregressive models Data analysis Iterative methods Outliers (statistics) Physics Statistical analysis
Online-Zugang:	Volltext
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