A New Generalized Weighted Weibull Distribution

Salman Abbas, Gamze Ozal, Saman Hanif Shahbaz, Muhammad Qaiser Shahbaz

Abstract


In this article, we present a new generalization of weighted Weibull distribution using Topp Leone family of distributions. We have studied some statistical properties of the proposed distribution including quantile function, moment generating function, probability generating function, raw moments, incomplete moments, probability, weighted moments, Rayeni and q th entropy. The have obtained numerical values of the various measures to see the eect of model parameters. Distribution of of order statistics for the proposed model has also been obtained. The estimation of the model parameters has been done by using maximum likelihood method. The eectiveness of proposed model is analyzed by means of a real data sets. Finally, some concluding remarks are given.


Keywords


Weighted Weibull, Topp Leone family, Order Statistics, Entropy

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DOI: http://dx.doi.org/10.18187/pjsor.v15i1.2782

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Title

A New Generalized Weighted Weibull Distribution

Keywords

Weighted Weibull, Topp Leone family, Order Statistics, Entropy

Description

In this article, we present a new generalization of weighted Weibull distribution using Topp Leone family of distributions. We have studied some statistical properties of the proposed distribution including quantile function, moment generating function, probability generating function, raw moments, incomplete moments, probability, weighted moments, Rayeni and q th entropy. The have obtained numerical values of the various measures to see the eect of model parameters. Distribution of of order statistics for the proposed model has also been obtained. The estimation of the model parameters has been done by using maximum likelihood method. The eectiveness of proposed model is analyzed by means of a real data sets. Finally, some concluding remarks are given.


Date

2019-03-23

Identifier


Source

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



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