A new robust approach for the polytomous logistic regression model based on Rényi's pseudodistances.

IF 1.4 4区数学 Q3 BIOLOGY

Biometrics Pub Date : 2024-10-03 DOI:10.1093/biomtc/ujae125

Elena Castilla

引用次数: 0

Abstract

This paper presents a robust alternative to the maximum likelihood estimator (MLE) for the polytomous logistic regression model, known as the family of minimum Rènyi Pseudodistance (RP) estimators. The proposed minimum RP estimators are parametrized by a tuning parameter $\alpha \ge 0$, and include the MLE as a special case when $\alpha =0$. These estimators, along with a family of RP-based Wald-type tests, are shown to exhibit superior performance in the presence of misclassification errors. The paper includes an extensive simulation study and a real data example to illustrate the robustness of these proposed statistics.

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基于 Rényi 伪距的多项式逻辑回归模型新稳健方法。

本文提出了多态逻辑回归模型最大似然估计器（MLE）的稳健替代方法，即最小雷尼伪距（RP）估计器系列。所提出的最小 RP 估计器由一个调整参数 $\alpha \ge 0$ 参数化，并将 MLE 作为 $\alpha =0$ 时的特例。这些估计器以及一系列基于 RP 的沃尔德类型检验，在存在误分类误差的情况下表现出卓越的性能。论文包括一项广泛的模拟研究和一个真实数据示例，以说明这些拟议统计量的稳健性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Biometrics 生物-生物学

CiteScore

2.70

自引率

5.30%

发文量

178

审稿时长

4-8 weeks

期刊介绍： The International Biometric Society is an international society promoting the development and application of statistical and mathematical theory and methods in the biosciences, including agriculture, biomedical science and public health, ecology, environmental sciences, forestry, and allied disciplines. The Society welcomes as members statisticians, mathematicians, biological scientists, and others devoted to interdisciplinary efforts in advancing the collection and interpretation of information in the biosciences. The Society sponsors the biennial International Biometric Conference, held in sites throughout the world; through its National Groups and Regions, it also Society sponsors regional and local meetings.