摘要
文章针对线性回归问题中的模型选择进行了研究,从理论上提出了将k折交叉验证与投影预测法相结合的模型选择方法,通过数据仿真验证了此方法的合理性。
This paper studies the model selection in linear regression, and theoretically puts forward the model selection method by combining k-fold cross-validation and projection prediction method. Finally the paper verifies the rationality of this method by data simulation.
作者
井晓丹
朱永忠
井睿
Jing Xiaodan;Zhu Yongzhong;Jing Rui(College of Science,Hohai University,Nanjing 211100,China;College of Economics and Management,Northwest A &F University,Xianyang Shaanxi 712100,China)
出处
《统计与决策》
CSSCI
北大核心
2019年第1期29-33,共5页
Statistics & Decision
关键词
贝叶斯模型平均
交叉验证
投影预测
泛化能力
Bayesian model averaging
cross-validation
projection prediction
generalization ability