Power modified XLindley distribution: Statistical properties and applications

Yusra A. Tashkandy, M. E. Bakr, Sid Ahmed Benchiha, Laxmi Prasad Sapkota, Oluwafemi Samson Balogun, Getachew Tekle Mekiso, Eslam Hussam, Ahmed M. Gemeay

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

This research introduces a novel two-parameter distribution, the power-modified XLindley distribution, developed through the application of power transformation techniques to the existing modified XLindley distribution. This new distribution enhances flexibility and adaptability in statistical modeling. We conduct a thorough examination of its statistical properties, exploring its potential to improve data fitting and modeling accuracy. To assess the effectiveness of the model, we employ multiple estimation techniques and evaluate their performance through extensive simulation experiments. Our findings indicate that the maximum product of the spacings method is particularly effective for parameter estimation. To demonstrate the practical utility of the proposed model, we apply it to two real-world datasets: one related to flood data and the other to reliability engineering. The results underscore the distribution’s superior ability to capture the characteristics of these datasets compared to existing models, highlighting its significance for applications in natural disaster analysis and reliability studies.

Original languageEnglish
Article number20262
JournalScientific Reports
Volume14
Issue number1
DOIs
StatePublished - Dec 2024
Externally publishedYes

Keywords

  • Application
  • Estimation methods
  • Modified XLindley distribution
  • Moments

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