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.

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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

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article

The power new XLindley distribution: Statistical inference, fuzzy reliability, and applications

Caner Tanış, Yusra Tashkandy, Abdelali Ezzebsa, Halim Zeghdoudi et al.
13 citations
Heliyon
Statistical Distribution Estimation and Applications
9.22
article

The power new XLindley distribution: Statistical inference, fuzzy reliability, and applications

Caner Tanış, Yusra Tashkandy, Abdelali Ezzebsa, Halim Zeghdoudi, Anoop Kumar, M. E. Bakr, Ahmed M. Gemeay
article en
13 citations

Abstract

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.

HeliyonVol. 10(17)
Badji Mokhtar-Annaba University (DZ), Tanta University (EG), Çankırı Karatekin University (TR), King Saud University (SA), Central University of Haryana (IN)
King Saud University
Openalex Percentile: Top 2%
Statistical Distribution Estimation and Applications
9.22
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