Theoretical properties of Bayesian Student-t linear regression

被引：3

作者：

Gagnon, Philippe ^{[1
]}

Hayashi, Yoshiko ^{[2
]}

机构：

[1] Univ Montreal, Montreal, PQ, Canada

[2] Osaka Univ Econ, Osaka, Japan

来源：

STATISTICS & PROBABILITY LETTERS | 2023年 / 193卷

关键词：

Built-in robustness; Conflict resolution; Efficiency; Large-sample asymptotics; ROBUSTNESS; MODELS; OUTLIERS; LOCATION;

D O I：

10.1016/j.spl.2022.109693

中图分类号：

O21 [概率论与数理统计]; C8 [统计学];

学科分类号：

020208 ; 070103 ; 0714 ;

摘要：

Bayesian Student -t linear regression is a common robust alternative to the normal model, but its theoretical properties are not well understood. We aim to fill some gaps by providing analyses in two different asymptotic scenarios. The results allow to precisely characterize the trade-off between robustness and efficiency controlled through the degrees of freedom (at least asymptotically).(c) 2022 Elsevier B.V. All rights reserved.

引用

页数：8

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