Litcius/Paper detail

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

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

2024Heliyon16 citationsDOIOpen Access PDF

Abstract

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.

Topics & Concepts

Reliability (semiconductor)Statistical inferenceInferenceReliability engineeringComputer scienceFrequentist inferencePower (physics)MathematicsStatisticsArtificial intelligenceEngineeringBayesian inferencePhysicsBayesian probabilityThermodynamicsStatistical Distribution Estimation and ApplicationsProbabilistic and Robust Engineering DesignAdvanced Statistical Methods and Models
The power new XLindley distribution: Statistical inference, fuzzy reliability, and applications | Litcius