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Enhanced Real-Life Data Modeling with the Modified Burr III Odds Ratio–G Distribution

Authors :
Haochong Yang
Mingfang Huang
Xinyu Chen
Ziyan He
Shusen Pu
Source :
Axioms, Vol 13, Iss 6, p 401 (2024)
Publication Year :
2024
Publisher :
MDPI AG, 2024.

Abstract

In this study, we introduce the modified Burr III Odds Ratio–G distribution, a novel statistical model that integrates the odds ratio concept with the foundational Burr III distribution. The spotlight of our investigation is cast on a key subclass within this innovative framework, designated as the Burr III Scaled Inverse Odds Ratio–G (B-SIOR-G) distribution. By effectively integrating the odds ratio with the Burr III distribution, this model enhances both flexibility and predictive accuracy. We delve into a thorough exploration of this distribution family’s mathematical and statistical properties, spanning hazard rate functions, quantile functions, moments, and additional features. Through rigorous simulation, we affirm the robustness of the B-SIOR-G model. The flexibility and practicality of the B-SIOR-G model are demonstrated through its application to four datasets, highlighting its enhanced efficacy over several well-established distributions.

Details

Language :
English
ISSN :
20751680
Volume :
13
Issue :
6
Database :
Directory of Open Access Journals
Journal :
Axioms
Publication Type :
Academic Journal
Accession number :
edsdoj.88153cf6c5464eefb6469e6e7848a3d5
Document Type :
article
Full Text :
https://doi.org/10.3390/axioms13060401