计数数据贝尔分布的最大似然估计器的性能

Q3 Mathematics

Journal of Modern Applied Statistical Methods Pub Date : 2024-01-06 DOI:10.56801/jmasm.v23.i2.3

David E. Giles

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引用次数: 0

摘要

离散数据的单参数 "贝尔分布 "允许数据过度分散。在有限样本中，其参数的最大似然估计值存在向下偏差。我们考虑了减少这种偏差的各种方法。模拟研究表明，这些方法都很有效，而且还能小幅改善估计器的均方误差。Cox-Snell 修正法是我们所考虑的各种方案中的推荐选择。

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The Performance of the Maximum Likelihood Estimator for the Bell Distribution for Count Data

The single-parameter “Bell distribution” for discrete data allows for over-dispersion in the data. The maximum likelihood estimator for its parameter is downward-biased in finite samples. We consider various methods for reducing this bias. A simulation study shows that these are effective and also lead to a small improvement in the mean squared error of the estimator. The Cox-Snell correction is the recommended. choice among the options that are considered.

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来源期刊

Journal of Modern Applied Statistical Methods STATISTICS & PROBABILITY-

CiteScore

0.50

自引率

0.00%

发文量

期刊介绍： The Journal of Modern Applied Statistical Methods is an independent, peer-reviewed, open access journal designed to provide an outlet for the scholarly works of applied nonparametric or parametric statisticians, data analysts, researchers, classical or modern psychometricians, and quantitative or qualitative methodologists/evaluators.