Focused Information Criterion and Model Averaging with Generalized Rank Regression.
Focused Information Criterion and Model Averaging with Generalized Rank Regression.
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DOI：
10.1016/j.spl.2016.10.020
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发表时间：
2017-03
影响因子：
0.8
通讯作者：
Ma S
中科院分区：
文献类型：
--
作者：
Zhang Q;Duan X;Ma S
广义秩回归是一类基于因子空间的权重加权秩回归，为鲁棒估计提供了强有力的工具。本文首先建立了局部模型错配下广义秩回归的渐近性质。然后将广义秩回归应用于焦点信息准则和频率模型平均，并建立了它们的性质。
Generalized rank regression, which is a class of weighted rank regression with weights based on factor space, provides a powerful tool for conducting robust estimation. In this article, we first establish the asymptotic properties of generalized rank regression under local model misspecification. We then apply the generalized rank regression to the focus information criterion and frequentist model averaging and establish their properties.