A New Extension of the Topp–Leone-Family of Models with Applications to Real Data

Mustapha Muhammad (), Lixia Liu (), Badamasi Abba (), Isyaku Muhammad (), Mouna Bouchane (), Hexin Zhang () and Sani Musa ()
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Mustapha Muhammad: Guangdong University of Petrochemical Technology
Lixia Liu: Hebei Normal University
Badamasi Abba: Central South University
Isyaku Muhammad: University of Electronic Science and Technology of China
Mouna Bouchane: Hebei Normal University
Hexin Zhang: Hebei Normal University
Sani Musa: Sule Lamido University

Annals of Data Science, 2023, vol. 10, issue 1, No 11, 225-250

Abstract: Abstract In this article, we proposed a new extension of the Topp–Leone family of distributions. Some important properties of the model are developed, such as quantile function, stochastic ordering, model series representation, moments, stress–strength reliability parameter, Renyi entropy, order statistics, and moment of residual life. A particular member called new extended Topp–Leone exponential (NETLE) is discussed. Maximum likelihood estimation (MLE), least-square estimation (LSE), and percentile estimation (PE) are used for the model parameter estimation. Simulation studies were conducted using NETLE to assess the MLE, LSE, and PE performance by examining their bias and mean square error (MSE), and the result was satisfactory. Finally, the applications of the NETLE to two real data sets are provided to illustrate the importance of the NETLG families in practice; the data sets consist of daily new deaths due to COVID-19 in California and New Jersey, USA. The new model outperformed many other existing Topp–Leone’s and exponential related distributions based on the real data illustrations.

Keywords: Topp–Leone model; Moments; Renyi entropy; Stress–strength parameter; Maximum likelihood estimation; Least square estimation; Percentile estimation; 62E05; 62F10; 62F12 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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DOI: 10.1007/s40745-022-00456-y

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