Development of a new exponential generalized family of distribution with its properties and application
1 Training and Research Department, National Institute for Educational Planning and Administration Ondo, Nigeria.
2 Department of Statistics, School of Physical Sciences, Federal University of Technology Akure, Nigeria.
Review Article
World Journal of Advanced Research and Reviews, 2024, 22(02), 275–297
Publication history:
Received on 20 March 2024; revised on 01 May 2024; accepted on 03 May 2024
Abstract:
In the field of reliability analysis, the selection of an appropriate lifespan model is critical. With a multitude of lifetime distributions accessible, the hunt for a more suited distribution remains essential. In this paper, we offer a unique class of distributions derived from the notion of exponential generalization, improved with changes to boost flexibility. Our suggested distribution incorporates multiple hazard rate profiles, giving enhanced flexibility. Analytical characteristics including the rth moment, moment generating function, quantile function, distribution of order statistics, and Rényi entropy are obtained. Employing maximum likelihood estimation, we estimate the unknown parameters. Through simulation tests and analysis of real-world datasets, we exhibit the model's usefulness compared to five existing lifespan distributions, emphasising the better performance of the GAYUF distribution. This research underlines the GAYUF distribution as a better model in the field of lifespan analysis
Keywords:
Probability Distribution; Hazard Rate; Statistical Properties; Exponential Generalization; Maximum Likelihood Estimation
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Copyright © 2024 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution Liscense 4.0