Families of Extended Exponentiated Generalized Distributions and Applications of Medical Data Using Burr III Extended Exponentiated Weibull Distribution

Sajid Hussain, Mahmood Ul Hassan (), Muhammad Sajid Rashid and Rashid Ahmed
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Sajid Hussain: Department of Statistics, The Islamia University of Bahawalpur, Bahawalpur 63100, Pakistan
Mahmood Ul Hassan: Department of Statistics, Stockholm University, SE-106 91 Stockholm, Sweden
Muhammad Sajid Rashid: Department of Computer Science, The Islamia University of Bahawalpur, Bahawalpur 63100, Pakistan
Rashid Ahmed: Department of Statistics, The Islamia University of Bahawalpur, Bahawalpur 63100, Pakistan

Mathematics, 2023, vol. 11, issue 14, 1-24

Abstract: In this article, four new families named as Weibull extended exponentiated-X (WEE-X), Lomax extended exponentiated-X (LEE-X), Logistic extended exponentiated-X (LGCEE-X), and Burr III extended exponentiated-X (BIIIEE-X) with their quantile functions are proposed. The expressions for distribution function and density function of BIIIEE-X family are written in terms of linear combinations of the exponentiated densities based to parent model. New models, i.e., Weibul extended exponentiated Weibull (WEEW), Lomax extended exponentiated Weibull (LEEW), Logistic extended exponentiated Weibull (LGCEEW), and Burr III extended exponentiated-Weibull (BIIIEEW) distributions are derived, were plotted for functions of probability density and hazard rate at different levels of parameters. Some mathematical properties of the BIIIEEW model are disclosed. The maximum likelihood method for the BIIIEEW model are described. Numerical applications of the BIIIEEW model to disease of cancer datasets are provided.

Keywords: likelihood; Weibull; exponentiated; cancer disease; simulation; incomplete moments (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2023
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