Modeling COVID-19 Real Data Set by a New Extension of Haq Distribution-Reference-Cited by-同舟云学术

Modeling COVID-19 Real Data Set by a New Extension of Haq Distribution

Published:2023-03-28 Issue:4 Volume:12 Page:327
ISSN:2075-1680
Container-title:Axioms
language:en
Short-container-title:Axioms

Author:

Tashkandy Yusra¹^ORCID,Bakr Mahmoud E.¹,Gemeay Ahmed M.²^ORCID,Hussam Eslam³,Abd El-Raouf Mahmoud M.⁴^ORCID,Hossain Md Moyazzem⁵^ORCID

Affiliation:

1. Department of Statistics and Operations Research, College of Science, King Saud University, P.O. Box 2455, Riyadh 11451, Saudi Arabia

2. Department of Mathematics, Faculty of Science, Tanta University, Tanta 31527, Egypt

3. Department of Mathematics, Faculty of Science, Helwan University, Cairo 11795, Egypt

4. Basic and Applied Science Institute, Arab Academy for Science, Technology and Maritime Transport (AASTMT), Alexandria P.O. Box 1029, Egypt

5. School of Mathematics, Statistics and Physics, Newcastle University, Newcastle upon Tyne NE1 7RU, UK

Abstract

Modeling real-life pandemics is very important; this study focuses on introducing a new superior flexible extension of the asymmetric Haq distribution known as the power Haq distribution (PHD). The most fundamental mathematical properties are derived. We determine its parameters using ten estimation methods. The asymptotic behavior of its estimators is investigated through simulation, and a comparison is done to find out the most efficient method for estimating the parameters of the distribution under consideration. We use a sample for the COVID-19 data set to evaluate the proposed model’s performance and usefulness in fitting the data set in comparison to other well-known models.

Funder

King Saud University

Publisher

MDPI AG

Subject

Geometry and Topology,Logic,Mathematical Physics,Algebra and Number Theory,Analysis

Link

https://www.mdpi.com/2075-1680/12/4/327/pdf

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