ARIMA与ARIMAX模型在私人汽车拥有量预测中的应用  

Application of ARIMA and ARIMAX Models in Predicting Private Car Ownership

作　　者：张淑娴 ZHANG Shuxian(School of Mathematics and Physics,Anhui Jianzhu University,Hefei 230601,China)

机构地区：[1]安徽建筑大学数理学院,合肥230601

出　　处：《科技和产业》2024年第9期189-194,共6页Science Technology and Industry

基　　金：安徽省高等学校科学研究重点项目(2022AH050247);安徽建筑大学科研项目(2016QD118)。

摘　　要：为了提高私人汽车拥有量的预测精度,利用时间序列分析方法对全国2005—2020年的私人汽车拥有量数据进行研究,建立基于动态回归(ARIMAX)模型。运用Lasso模型和灰色关联分析得出影响私人汽车拥有量的主要因素,并将主要因素作为回归项引入差分自回归移动平均(ARIMA)模型。然后,在ARIMA模型的基础上建立ARIMAX模型。模型预测的对比结果揭示了ARIMAX的拟合效果更佳,适用于全国私人汽车拥有量的预测。In order to improve the prediction accuracy of private car ownership,the data of private car ownership in China from 2005 to 2020 is analyzed by using time series analysis method,and a prediction model based on dynamic regression(ARIMAX)model is established.Lasso model and grey correlation analysis are used to get the main factors affecting private car ownership,and the main factors are introduced into autoregressive integrated moving average(ARIMA)model as regression terms.The ARIMAX model is established on the basis of the ARIMA model.Through the comparison of model prediction,it is found that ARIMAX model has better fitting effect,which is suitable for the prediction of private car ownership in China.

关 键 词：动态回归(ARIMAX)模型 Lasso模型 私人汽车拥有量 

分 类 号：F542[经济管理—产业经济]