Novel Closed‐Form Point Estimators for a Weighted Exponential Family Derived From Likelihood Equations

IF 0.7 4区数学 Q3 STATISTICS & PROBABILITY

Stat Pub Date : 2024-08-28 DOI:10.1002/sta4.723

Roberto Vila, Eduardo Nakano, Helton Saulo

引用次数: 0

Abstract

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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从似然方程推导出的加权指数族新闭式点估计器

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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来源期刊

Stat Decision Sciences-Statistics, Probability and Uncertainty

CiteScore

1.10

自引率

0.00%

发文量

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