摘要
以1995年至2016年22个年度的社会消费品零售总额数据为例,结合Eviews软件通过识别、估计、诊断等过程实证分析这些数据的变化情况,建立能有效拟合其变化规律的时间序列预测模型,对未来几年的社会消费品零售总额进行预测,最终得到误差较小,短期预测较为准确的满意结果.
Taking total retail sales of social consumer goods in China as an example,through its identification,estimation,diagnosis,etc.,we use statistical software Eviews to establish a time series prediction model which can effectively fit the law of its change,predict the total retail sales of social consumer goods in the next few years,and finally get a satisfactory result with less error and more accurate short-term prediction.
作者
樊亮
FAN Liang(Department of Mathematics,Longnan Teachers College,Chengxian Gansu 742500)
出处
《甘肃高师学报》
2018年第2期18-20,共3页
Journal of Gansu Normal Colleges
基金
甘肃省教育科学研究所"十二五"规划课题"Frailty模型及其可靠性应用研究"(GS[2015]GHB0903)
关键词
社会消费品零售总额
时间序列预测模型
自相关函数
偏相关函数
total retail sales of social consumer goods
time series prediction model
autocorrelation function
partial correlation function