The Comparative Study on the Time Series Forecasting by Exponential Smoothing Techniques and Box-Jenkins Techniques : A Case Study of Forecasting the Export Values of Rice, Rubber and Cassava
Nicha Kaewhawong
Abstract
Nicha Kaewhawong
Abstract
The purpose of this research is to compare between two forecasting techniques, Exponential Smoothing Techniques and Box-Jenkins Techniques. In the study, the top three of Thai Agricultural Export Values, rice, rubber and cassava, were analyzed by the both techniques. The results were found that, the ARIMA model by Box-Jenkins Techniques is the best model which has the minimum error. Also, the error (from the ARIMA models) is corresponding with theoretical assumptions rather than the Exponential Smoothing models.
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The purpose of this research is to compare between two forecasting techniques, Exponential Smoothing Techniques and Box-Jenkins Techniques. In the study, the top three of Thai Agricultural Export Values, rice, rubber and cassava, were analyzed by the both techniques. The results were found that, the ARIMA model by Box-Jenkins Techniques is the best model which has the minimum error. Also, the error (from the ARIMA models) is corresponding with theoretical assumptions rather than the Exponential Smoothing models.
Key concepts: Exponential smoothing, Box–Jenkins, Autoregressive integrated moving average, Exponential function, Time series, Series (stratigraphy), Mathematics, Econometrics