Application of Time-series Decomposition with Dummy Variables to Cigarette Sales Forecast
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    Abstract:

    According to the long term and seasonal trends of time series, time-series decomposition makes a reasonable forecast of future, but when dealing with seasonal factors in China, it’ll be influenced by Chinese traditional festivals. Based on time-series decomposition, this paper built a modified model consisting of time-series decomposition and dummy variables which represent Chinese traditional festivals. In an example of the 90 months’ cigarette sales forecast in a province, the new model can effectively improve the prediction accuracy, and it’s helpful for enterprises to make production and sales plans.

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罗彪,闫维维,万亮.引入虚拟变量的时间序列分解法在卷烟销量预测中的应用.计算机系统应用,2012,21(12):215-220,148

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  • Received:April 23,2012
  • Revised:May 20,2012
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