k-Sample Bayesian Test for the Mean

Q1 Decision Sciences

Annals of Data Science Pub Date : 2026-03-20 DOI:10.1007/s40745-025-00668-y

Luai Al-Labadi, Ayman Alzaatreh

引用次数: 0

Abstract

In this article, a Bayesian alternative to the two-sample t-test and one-way ANOVA is proposed based on the Kullback-Leibler divergence and relative belief ratio. The new approach possesses attractive and desirable features since it can be calibrated, it provides evidence in favor of the null hypothesis, it allows checking the prior for prior-data conflict, and it maintains robustness in the analysis. Additionally, it does not require all populations to have a common variance. The utility of the approach is demonstrated through several examples in which it reflects its excellent performance.

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k-样本贝叶斯均值检验

本文提出了一种基于Kullback-Leibler散度和相对置信比的贝叶斯方法来替代双样本t检验和单因素方差分析。新方法具有吸引力和理想的特征，因为它可以校准，它提供了支持零假设的证据，它允许检查先验的先验数据冲突，并在分析中保持稳健性。此外，它并不要求所有的种群都有一个共同的方差。通过几个实例证明了该方法的实用性，并反映了其优异的性能。

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

Annals of Data Science Decision Sciences-Statistics, Probability and Uncertainty

CiteScore

6.50

自引率

0.00%

发文量

期刊介绍： Annals of Data Science (ADS) publishes cutting-edge research findings, experimental results and case studies of data science. Although Data Science is regarded as an interdisciplinary field of using mathematics, statistics, databases, data mining, high-performance computing, knowledge management and virtualization to discover knowledge from Big Data, it should have its own scientific contents, such as axioms, laws and rules, which are fundamentally important for experts in different fields to explore their own interests from Big Data. ADS encourages contributors to address such challenging problems at this exchange platform. At present, how to discover knowledge from heterogeneous data under Big Data environment needs to be addressed. ADS is a series of volumes edited by either the editorial office or guest editors. Guest editors will be responsible for call-for-papers and the review process for high-quality contributions in their volumes.