Mallows Model Averaging Estimation for Linear Regression Model with Right Censored Data

被引：0
作者：
Zhong-qi Liang
Xiao-lin Chen
Yan-qiu Zhou
机构：
[1] Zhejiang Gongshang University,School of Statistics and Mathematics
[2] Qufu Normal University,School of Statistics
[3] Guangxi University of Science and Technology,School of Science
来源：
Acta Mathematicae Applicatae Sinica, English Series | 2022年 / 38卷
关键词：
model averaging; right censoring; asymptotic optimality; synthetic data; 62J05; 62N01;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
This paper is concerned with an optimal model averaging estimation for linear regression model with right censored data. The weights for model averaging are picked up via minimizing the Mallows criterion. Under some mild conditions, it is shown that the identified weights possess the property of asymptotic optimality, that is, the model averaging estimator corresponding to these weights achieves the lowest squared error asymptotically. Some numerical studies are conducted to evaluate the finite-sample performance of our method and make comparisons with its intuitive competitors, while an application to the PBC dataset is provided to serve as an illustration.
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页码：5 / 23
页数：18
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