Cross Validation Based Model Averaging for Varying-Coefficient Models with Response Missing at Random  

作　　者：Huixin Li Xiuli Wang Huixin Li;Xiuli Wang(School of Mathematics and Statistics, Shandong Normal University, Jinan, China)

机构地区：[1]School of Mathematics and Statistics, Shandong Normal University, Jinan, China

出　　处：《Journal of Applied Mathematics and Physics》2024年第3期764-777,共14页应用数学与应用物理（英文）

摘　　要：In this paper, a model averaging method is proposed for varying-coefficient models with response missing at random by establishing a weight selection criterion based on cross-validation. Under certain regularity conditions, it is proved that the proposed method is asymptotically optimal in the sense of achieving the minimum squared error.In this paper, a model averaging method is proposed for varying-coefficient models with response missing at random by establishing a weight selection criterion based on cross-validation. Under certain regularity conditions, it is proved that the proposed method is asymptotically optimal in the sense of achieving the minimum squared error.

关 键 词：Response Missing at Random Model Averaging Asymptotic Optimality B-Spline Approximation 

分 类 号：O17[理学—数学]