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二元逻辑回归模型中的一阶近似刀切修正岭型估计

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在二元逻辑回归模型中,基于一阶近似修正岭型估计方法和刀切法提出了一类新估计,即一阶近似刀切修正岭型估计,探讨得到了新估计在均方误差等准则下优于一阶近似修正岭型估计、一阶近似极大似然估计的充分条件,同时通过数值模拟和实证分析对部分理论结果进行了说明,结果显示,当满足理论结果中的条件时,一阶近似刀切修正岭型估计在相关准则下优于一阶近似修正岭型估计、一阶近似极大似然估计.
First-order approximate jackknifed modified ridge-type estimator in binary logistic regression model
In the binary logistic regression model, a new type of estimator is proposed based on the first-order approximate modified ridge-type estimator method and the jackknife method. The sufficient conditions for the new estimator to be better than the first-order approximate modified ridge-type estimator and the first-order approximate maximum likelihood estimator under the criteria such as mean square error are discussed. At the same time, some of the theoretical results are illustrated by numerical simulation and empirical analysis. The results show that when the conditions in the theoretical results are met, the first-order approximate jackknifed ridge-type estimator is superior to the first-order approximate modified ridge-type estimator and first-order approximate maximum likelihood estimator under relevant criteria.

binary logistic regression modelmulticollinearityfirst order approximated jackknifed modified ridge-type estimatorjackknifemean square error

肖松、黄介武

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贵州民族大学 数据科学与信息工程学院,贵州 贵阳,550025

二元逻辑回归模型 多重共线性 一阶近似刀切修正岭型估计 刀切法 均方误差

贵州省高等学校大数据分析与智能计算重点实验室项目贵州省高等学校光通讯系统中孤子的数学理论与计算协作创新团队项目

黔教技[2023]012号黔教技[2023]062号

2024

10.3969/j.issn.1672-6146.2024.02.002

湖南文理学院学报(自然科学版)
湖南文理学院

湖南文理学院学报(自然科学版)

CHSSCD
影响因子：0.274
ISSN：1672-6164
年,卷(期)：2024.36(2)