我国社会消费品饮食类零售总额的预测模型研究

The Forecasting Model of Time Series for Total Retail Sales of Consumer Goods Food Categories in China

文章运用时间序列乘积季节模型,在SPSS系统下对我国2004年1月至2009年12月共72个月份的社会消费品饮食类零售总额进行实证分析,从模型识别、参数估计、适应性检验和实际拟合4个方面确定了无常数项的统计预测模型,并对模型的预测效果进行检验,结果分析表明,该模型能较好地反应零售总额的变化规律.

Under the SPSS system, this paper analysis the total retail sales of social consumer goods categories in China from January 2004 to December 2009 by applying the multiplicative seasonal model. From the model, identification, parameter estimation, adaptive testing and the actual fitting, we identifies a statistical forecasting models. The results of analysis showed that the model can better reflect the changes of the total retail sales.