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journal article·2023-09-01Open access

Modified XLindley distribution: Properties, estimation, and applications

Ahmed M. Gemeay, Abdelfateh Beghriche, Laxmi Prasad Sapkota, Halim Zeghdoudi, Nicholas Makumi, M. E. Bakr, Oluwafemi Samson Balogun

AIP Advances· Volume 13· Issue 9
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Source abstract

Abstract

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.
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Research context

OpenAlex topics: Statistical Distribution Estimation and Applications · Probabilistic and Robust Engineering Design · Hydrology and Drought Analysis

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Department of Mathematics, Faculty of Science, Tanta University 1 , Tanta 31527, Egypt

Department of Mathematics, Faculty of Exact Sciences, University the Brothers Mentouri Constantine 1 2 , Constantine 25019, Algeria

Department of Statistics, Tribhuvan University, Tribhuvan Multiple Campus 3 , Palpa, Nepal

LaPS Laboratory, Badji Mokhtar–Annaba University 4 , Annaba 23000, Algeria

Pan African University, Institute for Basic Sciences, Technology and Innovation (PAUSTI) 5 , Nairobi, Kenya

Department of Statistics and Operations Research, College of Science, King Saud University 6 , P.O. Box 2455, Riyadh 11451, Saudi Arabia

Department of Computing, University of Eastern Finland 7 , Kuopio FI-70211, Finland

Funding

King Saud University

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