基于组合模型的云南省卷烟需求预测与结果评价研究
|
摘要
本文提出了一种适合云南烟草行业需求预测的方法体系,构建了优化的回归预测模型和时间序列预测模型,对云南省卷烟需求量进行预测:在数据处理阶段,对价值量指标进行CPI还原;在指标选择阶段,运用时差相关分析和简单相关分析确定宏观经济指标;在模型构建阶段,运用先行两期的宏观经济数据预测当期卷烟销量,并运用最小二乘法计算回归预测模型和时间序列预测模型的权重;在对模型稳定性评价阶段,以建模预测结果的平均相对误差及置信度为基础,构建了一套适合云南卷烟需求预测的模型评判标准,并根据云南实际对模型的稳定性进行评价。
In this paper, a system suitable for Yunnan tobacco industry demand forecasting was proposed, and an optimized regression prediction model and time series prediction model were constructed to predict cigarette demand in Yunnan province. In data processing stage, CPI reduction was carried out for value index. In the stage of index selection, time difference correlation analysis and simple correlation analysis were carried out to determine macroeconomic indicators In the model construction stage, the ?rst two periods of macroeconomic data were used to forecast current cigarette sales, and weights of the regression model and time series prediction model were calculated by least squares method. In the evaluation stage of model stability, a set of criteria for evaluating forecast of cigarettes in Yunnan was constructed based on average relative error and con?dence of model predictive results, and the stability of the model was evaluated according to actual situation of Yunnan province.
In this paper, a system suitable for Yunnan tobacco industry demand forecasting was proposed, and an optimized regression prediction model and time series prediction model were constructed to predict cigarette demand in Yunnan province. In data processing stage, CPI reduction was carried out for value index. In the stage of index selection, time difference correlation analysis and simple correlation analysis were carried out to determine macroeconomic indicators In the model construction stage, the ?rst two periods of macroeconomic data were used to forecast current cigarette sales, and weights of the regression model and time series prediction model were calculated by least squares method. In the evaluation stage of model stability, a set of criteria for evaluating forecast of cigarettes in Yunnan was constructed based on average relative error and con?dence of model predictive results, and the stability of the model was evaluated according to actual situation of Yunnan province.
引文
[1]白远良,吴应禄,程晓苏.我国卷烟需求分析(上、下)-需求现状与模型构建[J].中国烟草学报,2007,13(3):96-101.BAI Yuanliang,WU Yinglu,CHENG Xiaosu.An analysis of cigarette demand in China(ⅠandⅠ)-current status and model building[J].Acta Tabacaria Sinica,2007,13(3):96-101.
[2]刘凯,赵旻.基于广义脉冲响应的云南省经济增长与卷烟市场运行动态相关性研究[J].中国统计学会烟草分会,2015.Liu Kai,Zhao Min.Research on dynamic interactions between yunnan province’s economic growth and cigarette market based on generalized impulse response function[C].Tobacco Branch of The National Statistical Society of China,2015.
[3]赵旻.基于PCA主成分分析的云南卷烟销售与云南经济关系研究[J].中国统计学会烟草分会.2015.Zhao Min.Research on the relationship between cigarette market and macro economy based on PCA principal component analysis[C].Tobacco Branch of The National Statistical Society of China,2015.
[4]潘志刚,韩颖.组合预测法在我国汽车市场需求预测中的应用[J].商业研究,2006(20):126-129.Pan Zhigang,Han Ying.The Application of combinatorial forecast on china automobile market demand[J].Commercial Research,2006(20):126-129.
[5]单锐,王淑花,高东莲,等.基于时间序列模型与灰色模型的组合预测模型的研究[J].燕山大学学报,2012,36(1):79-83.Shan Rui,Wang Shuhua,Gao Donglian,et al.Research of combined forecasting model based on time series model and gray model[J].Journal of Yanshan University,2012,36(1):79-83.
[6]刘媛媛.中国入境旅游业的市场需求分析及预测[D].武汉大学硕士研究生毕业论文,2005.Liu Yuanyuan.Analyzing and forecasting market demand in Chinese inbound tourism[D].Master's Thesis of Wuhan University,2005.
[7]汤兆平,孙剑萍,杜相,等.基于ARIMA模型的N铁路局管内物流需求预测研究[J].经济问题探索,2014(7):76-81.
[8]李隽波,孙丽娜.基于多元线性回归分析的冷链物流需求预测[J].安徽农业科学,2011,39(11):6519-6520.Li Yibo,Sun Lina.Demand forecast of the cold chain logistics based on the multiple linear regression analysis[J].Journal of Anhui Agricultural Sciences,2011,39(11):6519-6520.
[9]卢惠林.组合预测模型的权重确定方法的研究[D].哈尔滨工业大学,2010.Huilin Lu.The study on the determination of weights for the combination forecasting model[D].Harbin Institute of Technology,2010.
[10]Li Jiahan,Chen Weiye.Forecasting macroeconomic time series:LASSO-based approaches and their forecast combinations with dynamic factor models[J].International Journal of Forecasting.2014.
[11]Matteo Kalchschmidt.The role of the forecasting process in improving forecast accuracy and operational performance[J].Pamela Danese,International Journal of Production Economics.2010(1).
[2]刘凯,赵旻.基于广义脉冲响应的云南省经济增长与卷烟市场运行动态相关性研究[J].中国统计学会烟草分会,2015.Liu Kai,Zhao Min.Research on dynamic interactions between yunnan province’s economic growth and cigarette market based on generalized impulse response function[C].Tobacco Branch of The National Statistical Society of China,2015.
[3]赵旻.基于PCA主成分分析的云南卷烟销售与云南经济关系研究[J].中国统计学会烟草分会.2015.Zhao Min.Research on the relationship between cigarette market and macro economy based on PCA principal component analysis[C].Tobacco Branch of The National Statistical Society of China,2015.
[4]潘志刚,韩颖.组合预测法在我国汽车市场需求预测中的应用[J].商业研究,2006(20):126-129.Pan Zhigang,Han Ying.The Application of combinatorial forecast on china automobile market demand[J].Commercial Research,2006(20):126-129.
[5]单锐,王淑花,高东莲,等.基于时间序列模型与灰色模型的组合预测模型的研究[J].燕山大学学报,2012,36(1):79-83.Shan Rui,Wang Shuhua,Gao Donglian,et al.Research of combined forecasting model based on time series model and gray model[J].Journal of Yanshan University,2012,36(1):79-83.
[6]刘媛媛.中国入境旅游业的市场需求分析及预测[D].武汉大学硕士研究生毕业论文,2005.Liu Yuanyuan.Analyzing and forecasting market demand in Chinese inbound tourism[D].Master's Thesis of Wuhan University,2005.
[7]汤兆平,孙剑萍,杜相,等.基于ARIMA模型的N铁路局管内物流需求预测研究[J].经济问题探索,2014(7):76-81.
[8]李隽波,孙丽娜.基于多元线性回归分析的冷链物流需求预测[J].安徽农业科学,2011,39(11):6519-6520.Li Yibo,Sun Lina.Demand forecast of the cold chain logistics based on the multiple linear regression analysis[J].Journal of Anhui Agricultural Sciences,2011,39(11):6519-6520.
[9]卢惠林.组合预测模型的权重确定方法的研究[D].哈尔滨工业大学,2010.Huilin Lu.The study on the determination of weights for the combination forecasting model[D].Harbin Institute of Technology,2010.
[10]Li Jiahan,Chen Weiye.Forecasting macroeconomic time series:LASSO-based approaches and their forecast combinations with dynamic factor models[J].International Journal of Forecasting.2014.
[11]Matteo Kalchschmidt.The role of the forecasting process in improving forecast accuracy and operational performance[J].Pamela Danese,International Journal of Production Economics.2010(1).
© 2004-2018 中国地质图书馆版权所有 京ICP备05064691号 京公网安备11010802017129号 地址：北京市海淀区学院路29号 邮编：100083 电话：办公室：(+86 10)66554848；文献借阅、咨询服务、科技查新：66554700 |