Statistical Modeling Using a New Distribution with Application in Health Data

Alanazi Talal Abdulrahman, Etaf Alshawarbeh and Mahmoud M. Abd El-Raouf ()
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Alanazi Talal Abdulrahman: Department of Mathematics, College of Science, University of Ha’il, Ha’il P.O. Box 55476, Saudi Arabia
Etaf Alshawarbeh: Department of Mathematics, College of Science, University of Ha’il, Ha’il P.O. Box 55476, Saudi Arabia
Mahmoud M. Abd El-Raouf: Basic and Applied Science Institute, Arab Academy for Science, Technology and Maritime Transport (AASTMT), Alexandria P.O. Box 1029, Egypt

Mathematics, 2023, vol. 11, issue 14, 1-18

Abstract: The modeling of pandemics is significant in understanding and addressing the spread of infectious diseases. This study introduces a novel and highly flexible extension of the asymmetric unit Burr–Hatke distribution, termed the power Burr–Hatke distribution (PUBHD), and comprehensively investigates its mathematical properties. Multiple parameter estimation methods are employed, and their asymptotic behavior is analyzed through simulation experiments. The different estimation techniques are compared to identify the most efficient approach for estimating the distribution’s parameters. To demonstrate the applicability and usefulness of the PUBHD model, we conducted a case study using a sample from the COVID-19 dataset and compared its performance with other established models. Our findings show that the PUBHD model provides a superior fit to the COVID-19 dataset and offers a valuable tool for accurately modeling real-life pandemics.

Keywords: COVID-19; Burr–Hatke distribution; simulation; estimation; modeling (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2023
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