Modified XLindley distribution: Properties, estimation, and applications

Autor: Ahmed M. Gemeay, Abdelfateh Beghriche, Laxmi Prasad Sapkota, Halim Zeghdoudi, Nicholas Makumi, M. E. Bakr, Oluwafemi Samson Balogun
Jazyk: angličtina
Rok vydání: 2023
Předmět:
Zdroj: AIP Advances, Vol 13, Iss 9, Pp 095021-095021-17 (2023)
Druh dokumentu: article
ISSN: 2158-3226
DOI: 10.1063/5.0172056
Popis: This article aims to introduce the inverse new XLindley distribution, a further extension of the new XLindley distribution. The article explores various properties of the proposed model, such as the quantile function, stochastic orders, entropies, fuzzy reliability, moments, and stress–strength estimation. The paper also compares different methods of estimating the parameters of the proposed model and evaluates their performance using a simulation study. Moreover, the paper demonstrates the usefulness of the proposed model by applying it to two real datasets. The article shows that the proposed model fits the data better than seven existing models based on model selection criteria, goodness-of-fit test statistics, and graphical visualizations. The paper concludes that the new model can be a valuable tool for modeling and analyzing hazard functions or survival data in various fields and contributing to probability theory and statistical inferences.
Databáze: Directory of Open Access Journals