The Exponentiated Generalized Topp Leone-G Family of Distributions: Properties and Applications

Hesham Mohamed Reyad, Morad Alizadeh, Farrukh Jamal, Soha Othman, G G Hamedani

Abstract


In this paper, we propose a new class of continuous distributions called the exponentiated generalized Topp Leone-G family that extends the Topp Leone-G family introduced by Al-Shomrani et al. (2016). We derive explicit expressions for certain mathematical properties of the new family such as; ordinary and incomplete moments, generating functions, reliability analysis, Lorenz and Bonferroni curves, Rényi entropy, stress strength model, moment of residual and reversed residual life, order statistics and extreme values. We discuss the maximum likelihood estimates and the observed information matrix for the model parameters. Two real data sets are used to illustrate the flexibility of the new family.


Keywords


Exponentiated Generalized-G family, Maximum Likelihood Estimation, Moments, Order Statistics, Topp Leone-G family.

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DOI: http://dx.doi.org/10.18187/pjsor.v15i1.2166

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Title

The Exponentiated Generalized Topp Leone-G Family of Distributions: Properties and Applications

Keywords

Exponentiated Generalized-G family, Maximum Likelihood Estimation, Moments, Order Statistics, Topp Leone-G family.

Description

In this paper, we propose a new class of continuous distributions called the exponentiated generalized Topp Leone-G family that extends the Topp Leone-G family introduced by Al-Shomrani et al. (2016). We derive explicit expressions for certain mathematical properties of the new family such as; ordinary and incomplete moments, generating functions, reliability analysis, Lorenz and Bonferroni curves, Rényi entropy, stress strength model, moment of residual and reversed residual life, order statistics and extreme values. We discuss the maximum likelihood estimates and the observed information matrix for the model parameters. Two real data sets are used to illustrate the flexibility of the new family.


Date

2019-03-22

Identifier


Source

Pakistan Journal of Statistics and Operation Research; Vol. 15 No. 1, 2019



Print ISSN: 1816-2711 | Electronic ISSN: 2220-5810