The exponentiated Half-Logistic-Type II Topp-Leone-G family of distribution with applications

Sengweni, Whatmore; Oluyede, Broderick; Rannona, Kethamile

doi:10.47974/JSMS-938

Open Access Research Article

The exponentiated Half-Logistic-Type II Topp-Leone-G family of distribution with applications

^*Whatmore SengweniCorresponding authorwhatmore.sengweni@studentmail.biust.ac.bwDepartment of Mathematics and Statistical SciencesBotswana International University of Science and TechnologyPalapye, BotswanaView full profile → , Broderick Oluyedeoluyedeo@biust.ac.bwDepartment of Mathematics and Statistical SciencesBotswana International University of Science and TechnologyPalapye, BotswanaView full profile → , Kethamile RannonaDepartment of Mathematics and Statistical SciencesBotswana International University of Science and TechnologyPalapye, BotswanaView full profile →

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pp. 853–876Vol. 27Issue 5July 2024DOI: 10.47974/JSMS-938XML

Received:: 08 Sep 2021
Accepted:: 05 Apr 2022
Published Online:: 27 May 2024
Article type:: Research Article
Language:: EN
Article no.:: JSMS-938
Pages:: 853–876

Abstract

The development and application of a new family of distributions is of tremendous practical importance. In this note, a new distribution called the exponentiated Half-Logistic-Type II Topp-Leone-G (EHL-TIITL-G) family is proposed and studied. We derive the statistical properties of this new family of distributions, including the moments, probability weighted moments, distribution of the order statistics and Rényi entropy. We investigated the various density and hazard rate function shapes of the EHL-TIITL-G model. The parameters of this new model have been estimated using the maximum likelihood technique. We conducted a simulation study to examine the bias and mean square error of the maximum likelihood estimators, and lastly, the potentiality of this new model has been demonstrated through the use of two real data sets.

Keywords

Generalized-G distribution Exponentiated distributions Half-logistic distribution Maximum likelihood estimation

Subject Classifications

62E9960E05

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