典型文献
Model Averaging Estimation for Varying-Coefficient Single-Index Models
文献摘要：
The varying-coefficient single-index model (VCSIM) is widely used in economics,statistics and biology.A model averaging method for VCSIM based on a Mallows-type criterion is proposed to improve prodictive capacity,which allows the number of candidate models to diverge with sample size.Under model misspecification,the asymptotic optimality is derived in the sense of achieving the lowest possible squared errors.The authors compare the proposed model averaging method with several other classical model selection methods by simulations and the corresponding results show that the model averaging estimation has a outstanding performance.The authors also apply the method to a real dataset.
文献关键词：
中图分类号：
作者姓名：
LIU Yue;ZOU Jiahui;ZHAO Shangwei;YANG Qinglong
作者机构：
School of Statistics,Jiangxi University of Finance and Economics,Nanchang 330013,China;School of Mathematical Sciences,University of Chinese Academy of Sciences,Beijing 100049,China;Academy of Mathematics and Systems Science,Chinese Academy of Sciences,Beijing 100190,China;School of Science,Minzu University of China,Beijing 100081,China;School of Statistics and Mathematics,Zhongnan University of Economics and Law,Wuhan 430073,China
文献出处：
引用格式：
[1]LIU Yue;ZOU Jiahui;ZHAO Shangwei;YANG Qinglong-.Model Averaging Estimation for Varying-Coefficient Single-Index Models)[J].系统科学与复杂性学报（英文版）,2022(01):264-282
A类：
VCSIM,prodictive,misspecification
B类：
Averaging,Estimation,Varying,Coefficient,Single,Index,Models,varying,coefficient,single,widely,used,economics,statistics,biology,averaging,Mallows,type,criterion,proposed,improve,capacity,which,number,candidate,models,diverge,sample,size,Under,asymptotic,optimality,derived,sense,achieving,lowest,possible,squared,errors,authors,compare,several,other,classical,selection,methods,by,simulations,corresponding,results,show,that,estimation,has,outstanding,performance,also,apply,real,dataset
AB值：
0.626737
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