从似然方程推导出的加权指数族新闭式点估计器

Pub Date : 2024-08-28 DOI:10.1002/sta4.723
Roberto Vila, Eduardo Nakano, Helton Saulo
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引用次数: 0

摘要

在本文中,我们提出并研究了加权指数族的闭式点估算器。我们还通过自举法开发了这些闭式估计器的减偏版本。我们使用蒙特卡罗模拟对估计器进行了评估,结果表明所提出的自举减偏估计器效果良好。我们利用两个真实数据集说明了所提出的方法。
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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Novel Closed‐Form Point Estimators for a Weighted Exponential Family Derived From Likelihood Equations
In this paper, we propose and investigate closed‐form point estimators for a weighted exponential family. We also develop a bias‐reduced version of these proposed closed‐form estimators through bootstrap methods. Estimators are assessed using a Monte Carlo simulation, revealing favourable results for the proposed bootstrap bias‐reduced estimators. We illustrate the proposed methodology with the use of two real data sets.
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