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
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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。
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来源期刊
Stat
Stat Decision Sciences-Statistics, Probability and Uncertainty
CiteScore
1.10
自引率
0.00%
发文量
85
期刊介绍: Stat is an innovative electronic journal for the rapid publication of novel and topical research results, publishing compact articles of the highest quality in all areas of statistical endeavour. Its purpose is to provide a means of rapid sharing of important new theoretical, methodological and applied research. Stat is a joint venture between the International Statistical Institute and Wiley-Blackwell. Stat is characterised by: • Speed - a high-quality review process that aims to reach a decision within 20 days of submission. • Concision - a maximum article length of 10 pages of text, not including references. • Supporting materials - inclusion of electronic supporting materials including graphs, video, software, data and images. • Scope - addresses all areas of statistics and interdisciplinary areas. Stat is a scientific journal for the international community of statisticians and researchers and practitioners in allied quantitative disciplines.
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