期刊名称：International Journal of Computer Trends and Technology
电子版ISSN：2231-2803
出版年度：2013
卷号：4
期号：8-1
出版社：Seventh Sense Research Group
摘要：In this paper an attempt is made to forecast the production of natural rubber in India by using monthly data for the period from January 1991 to December 2012. The comparative study of four different types of univariate time series models such as Linear Trend Equation, Additive Decomposition Model, Winter Seasonal Exponential Smoothing Model and Seasonal ARIMA Models were discussed. Mean Absolute Error (MAE), Mean Square Error (MSE), Mean Absolute Percentage Error (MAPE), Root Mean Square Error (RMSE) were used as the selection criteria to determine the best forecasting model. Seasonal ARIMA (2, 1, 2) (1, 1, 1)12 model for identification, parameter, estimation, diagnostic checking and forecasting future production. This study revealed that the time series data were influenced by a positive linear trend factor. It is therefore suggested that Additive decomposition could be used for forecasting the natural Rubber Production in India. The forecasting method for production of natural rubber production in India, as shown in this paper, can be a very useful tool for the Indian Rubber Industry Professionals and policy makers in India.
关键词：Decomposition; Exponential Smoothing; MAE; MAPE; SARIMA; Model Selection Criteria
