Modeling COVID-19 data with a novel neutrosophic Burr-III distribution.

Autor: Jamal F; Department of Statistics, The Islamia University of Bahawalpur, Bahawalpur, Pakistan., Shafiq S; Department of Statistics, The Islamia University of Bahawalpur, Bahawalpur, Pakistan., Aslam M; Department of Statistics, Faculty of Science, King Abdulaziz University, Jeddah, Saudi Arabia. aslam_ravian@hotmail.com., Khan S; Department of Statistics, The Islamia University of Bahawalpur, Bahawalpur, Pakistan., Hussain Z; Department of Statistics, The Islamia University of Bahawalpur, Bahawalpur, Pakistan., Abbas Q; Department of Statistics, The Islamia University of Bahawalpur, Bahawalpur, Pakistan.
Jazyk: angličtina
Zdroj: Scientific reports [Sci Rep] 2024 May 11; Vol. 14 (1), pp. 10810. Date of Electronic Publication: 2024 May 11.
DOI: 10.1038/s41598-024-61659-2
Abstrakt: In this study, we have presented a novel probabilistic model called the neutrosophic Burr-III distribution, designed for applications in neutrosophic surface analysis. Neutrosophic analysis allows for the incorporation of vague and imprecise information, reflecting the reality that many real-world problems involve ambiguous data. This ability to handle vagueness can lead to more robust and realistic models especially in situation where classical models fall short. We have also explored the neutrosophic Burr-III distribution in order to deal with the ambiguity and vagueness in the data where the classical Burr-III distribution falls short. This distribution offers valuable insights into various reliability properties, moment expressions, order statistics, and entropy measures, making it a versatile tool for analyzing complex data. To assess the practical relevance of our proposed distribution, we applied it to real-world data sets and compared its performance against the classical Burr-III distribution. The findings revealed that the neutrosophic Burr-III distribution outperformed than the classical Burr-III distribution in capturing the underlying data characteristics, highlighting its potential as a superior modeling toolin various fields.
(© 2024. The Author(s).)
Databáze: MEDLINE
Externí odkaz:
Nepřihlášeným uživatelům se plný text nezobrazuje