摘要
选取7个影响吉林省农业总产值的因素,运用SAS软件建立了农业总产值的多元回归模型。为解决经典线性回归模型的多重共线性问题,运用主成分回归模型和岭回归模型对其进行了修正,最后对这两个修正模型进行了比较分析,得出岭回归模型相对较优的结论。
Seven factors influencing agricultural output of Jilin Province are selected and then the multiple regression model for the output is established with SAS software.To solve the multicollinearity problem in the classical linear regression model,we adjust the model with both the principal component regression and ridge regression model.The improved the models are compared and it comes to a conclusion that the ridge regression has better performance.
出处
《长春工业大学学报》
CAS
2017年第1期1-7,共7页
Journal of Changchun University of Technology
基金
国家自然科学基金资助项目(11301037
11571051)
吉林省教育厅"十三五"规划项目(2016317)
关键词
SAS软件
多重共线性
主成分回归
岭回归
SAS software
multicollinearity
principal component regression
ridge regression