The Power XLindley Distribution: Statistical Inference, Fuzzy Reliability, and COVID-19 Application

Author:

Meriem Bouhadjar1,Gemeay Ahmed M.2ORCID,Almetwally Ehab M.3ORCID,Halim Zeghdoudi1ORCID,Alshawarbeh Etaf4,Abdulrahman Alanazi Talal4ORCID,El-Raouf M. M. Abd5ORCID,Hussam Eslam6ORCID

Affiliation:

1. LaPS Laboratory, Badji Mokhtar University, Annaba, Algeria

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

3. Department of Statistics, Faculty of Business Administration, Delta University of Science and Technology, Gamasa 11152, Egypt

4. Department of Mathematics, College of Science University of Ha’il, Hail, Saudi Arabia

5. Basic and Applied Science Institute, Arab Academy for Science, Technology and Maritime Transport (AASTMT), Alexandria, Egypt

6. Department of Mathematics, Faculty of Science, Helwan University, Cairo, Egypt

Abstract

The power XLindley (PXL) distribution is introduced in this study. It is a two-parameter distribution that extends the XLindley distribution established in this paper. Numerous statistical characteristics of the suggested model were determined analytically. The proposed model’s fuzzy dependability was statistically assessed. Numerous estimation techniques have been devised for the purpose of estimating the proposed model parameters. The behaviour of these factors was examined using randomly generated data and developed estimation approaches. The suggested model seems to be superior to its base model and other well-known and related models when applied to the COVID-19 data set.

Funder

Research Deanship in University of Ha’il

Publisher

Hindawi Limited

Subject

Analysis

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