The power new XLindley distribution: Statistical inference, fuzzy reliability, and applications
This paper introduces the power new XLindley (PNXL) distribution, a novel two-parameter distribution derived using the power transformation method applied to the XLindley distribution. We thoroughly explore the structural properties of the PNXL distribution, including the <i>r</i>th moment about the origin, moment generating function, survival rate function, distribution function, hazard rate function, skewness, kurtosis, and coefficient of variation. Additionally, we derive the quantile function, fuzzy reliability, reliability measures, stochastic ordering, and actuarial measures for this new distribution. To estimate the parameters of the PNXL distribution, we propose several estimators and evaluate their performance through extensive simulation studies. To demonstrate the applicability and superiority of the PNXL distribution over existing distributions, we fit it to two real datasets and compare its performance with potential competing models. The results highlight the PNXL distribution's effectiveness and potential as a robust tool for modeling and analyzing real-world data.
Authors
- Caner Tanış (ORCID: https://orcid.org/0000-0003-0090-1661)
- Yusra Tashkandy (ORCID: https://orcid.org/0000-0003-2878-4460)
- Abdelali Ezzebsa
- Halim Zeghdoudi (ORCID: https://orcid.org/0000-0002-4759-5529)
- Anoop Kumar (ORCID: https://orcid.org/0000-0003-2775-6548)
- M. E. Bakr (ORCID: https://orcid.org/0000-0003-3493-033X)
- Ahmed M. Gemeay (ORCID: https://orcid.org/0000-0001-6767-4016)
Institutions
- Badji Mokhtar-Annaba University (DZ)
- Tanta University (EG)
- Çankırı Karatekin University (TR)
- King Saud University (SA)
- Central University of Haryana (IN)
Publication Details
- Journal
- Heliyon
- Published
- 2024-08-23
- DOI
- https://doi.org/10.1016/j.heliyon.2024.e36594
- Citations
- 13
- Primary Topic
- Statistical Distribution Estimation and Applications
- Type
- article
- Field-Weighted Citation Impact
- 9.22
Funders
- King Saud University