A proposed Technique for the Problem of Selection  best Forecasting Model in Time Series: A Case Study

R. Muttar, Thafer

doi:10.33899/iqjoss.2008.31409

	A proposed Technique for the Problem of Selection best Forecasting Model in Time Series: A Case Study
IRAQI JOURNAL OF STATISTICAL SCIENCES
Article 2, Volume 8, Issue 2, 2008, Pages 1-20 PDF (0 K)
DOI: 10.33899/iqjoss.2008.31409
Author
Thafer R. Muttar
Abstract
Forecasting is Considered as one of the essential goals regarding time series analysis, and forecasting accuracy decreases the risk possibility regarding decision making. Whereat the best model to represent the time series data, might not be the same model used for forecasting. The forecasting evaluation criterion used such as RMSE, MAPE, and MAE provides almost different results concerning one time series, which confuse the researcher to select the best model for forecasting. Therefore this research deals with the problems of criterion differences results, that effects the evaluation performance to select the best model, and providing a statistical manner that employs the forecasting criterion results that mentioned as a weighted mean for each model of ARIMA which is considered as a candidate model with the leased weighted mean that provides the best forecasting performance. This has been applied on the monthly time series for the water of the Tigris River (M-cu-m) that enters to Mosul City for the period 1963-1995. Meanwhile Box-Jenkins model shows SARIMA (1,1,2) * (3,1,1) 12Very encouraging forecasting results depending on the suggested manner compared with the rest of models, meanwhile the best model for representing the data is SARIMA (1,1,2) * (0,1,1) 12 .

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