Bayesian Estimation of Variance-Based Information Measures and Their Application to Testing Uniformity

Autor:	Luai Al-Labadi, Mohammed Hamlili, Anna Ly
Jazyk:	angličtina
Rok vydání:	2023
Předmět:	Bayesian nonparametric inference entropy extropy information theory goodness-of-fit tests Mathematics QA1-939
Zdroj:	Axioms, Vol 12, Iss 9, p 887 (2023)
Druh dokumentu:	article
ISSN:	2075-1680
DOI:	10.3390/axioms12090887
Popis:	Entropy and extropy are emerging concepts in machine learning and computer science. Within the past decade, statisticians have created estimators for these measures. However, associated variability metrics, specifically varentropy and varextropy, have received comparably less attention. This paper presents a novel methodology for computing varentropy and varextropy, drawing inspiration from Bayesian nonparametric methods. We implement this approach using a computational algorithm in R and demonstrate its effectiveness across various examples. Furthermore, these new estimators are applied to test uniformity in data.
Databáze:	Directory of Open Access Journals
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