具有任意脆弱性的Cox模型中部分似然估计量的缩放Fisher一致性

IF 0.4 4区 数学 Q4 STATISTICS & PROBABILITY Probability and Mathematical Statistics-Poland Pub Date : 2020-01-01 DOI:10.37190/0208-4147.41.1.6
T. Bednarski, P. Nowak
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引用次数: 1

摘要

本文认为,基于Cox回归模型和部分似然估计的推理对于模型的各种扩展是可能的,特别是包括任意脆弱变量。我们证明了在解释变量的对称型分布假设下,这种一般设置下的估计量在比例因子上是Fisher一致的。模拟实验显示了估计器的典型行为,以及基于不同Cox模型扩展的Anderson-Darling统计量的拟合检验。2020数学学科分类:小学62N01;二次62 f12。
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Scaled Fisher consistency of partial likelihood estimator in the Cox model with arbitrary frailty
It is argued that inference based on the Cox regression model and the partial likelihood estimator is possible for various extensions of the model, which in particular include an arbitrary frailty variable. We demonstrate that the estimator in such a general setup is Fisher consistent up to a scaling factor under symmetry type distributional assumptions on explanatory variables. A simulation experiment shows exemplary behaviour of the estimator and also of a test of fit based on the Anderson–Darling statistic for different Cox model extensions. 2020 Mathematics Subject Classification: Primary 62N01; Secondary 62F12.
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来源期刊
CiteScore
0.70
自引率
0.00%
发文量
0
审稿时长
>12 weeks
期刊介绍: PROBABILITY AND MATHEMATICAL STATISTICS is published by the Kazimierz Urbanik Center for Probability and Mathematical Statistics, and is sponsored jointly by the Faculty of Mathematics and Computer Science of University of Wrocław and the Faculty of Pure and Applied Mathematics of Wrocław University of Science and Technology. The purpose of the journal is to publish original contributions to the theory of probability and mathematical statistics.
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