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Annals of Data Science

Erschienen in:

20.02.2019

On Exponential Negative-Binomial-X Family of Distributions

verfasst von: Zawar Hussain, Muhammad Aslam, Zahid Asghar

Erschienen in: Annals of Data Science | Ausgabe 4/2019

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Abstract

This paper introduces a new family of distributions using exponential negative binomial distribution. The proposed family of distributions generalizes the Marshall–Olkin, Complementary exponential G-geometric, Complementary Beta G-geometric and Complementary Kumaraswamy G-geometric families of distribution. Explicit expressions of statistical and reliability properties of the proposed family of distributions are derived. Some special cases of this family of distributions are presented in detail. Suitability of the suggested family of distributions is established by using real life data sets from different areas of application. The empirical results indicate that the proposed family performs better than already existing families of distributions.

Vorheriger Artikel Alpha-Power Transformed Lindley Distribution: Properties and Associated Inference with Application to Earthquake Data

Nächster Artikel Estimation and Prediction for Gompertz Distribution Under the Generalized Progressive Hybrid Censored Data

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Titel: On Exponential Negative-Binomial-X Family of Distributions
verfasst von: Zawar Hussain
Muhammad Aslam
Zahid Asghar
Publikationsdatum: 20.02.2019
Verlag: Springer Berlin Heidelberg
Erschienen in: Annals of Data Science / Ausgabe 4/2019
Print ISSN: 2198-5804
Elektronische ISSN: 2198-5812
DOI: https://doi.org/10.1007/s40745-019-00194-8

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