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Annals of Data Science

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12.03.2018

Transmuted Kumaraswamy Quasi Lindley Distribution with Applications

verfasst von: M. Elgarhy, I. Elbatal, Muhammad Ahsan ul Haq, Amal S. Hassan

Erschienen in: Annals of Data Science | Ausgabe 4/2018

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Abstract

The Lindley distribution is one of the widely used models for studying most of reliability modeling. Besides, several of researchers have motivated new classes of distributions based on modifications of the quasi Lindley distribution. In this article, a new version of generalized distributions named as the transmuted Kumaraswamy quasi Lindley (TKQL) is introduced. Various statistical properties of the TKQL distribution are provided. The rth moment of the TKQL distribution and its moment generating function are explored. Moreover, estimation of the model parameters is discussed via the method of maximum likelihood. Applications to real data are performed to clarify the flexibility of the TKQL distribution in comparison with some sub-models.

Vorheriger Artikel Fractal Dimension Calculation for Big Data Using Box Locality Index

Nächster Artikel Exponentiated Power Lindley Logarithmic: Model, Properties and Applications

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Titel: Transmuted Kumaraswamy Quasi Lindley Distribution with Applications
verfasst von: M. Elgarhy
I. Elbatal
Muhammad Ahsan ul Haq
Amal S. Hassan
Publikationsdatum: 12.03.2018
Verlag: Springer Berlin Heidelberg
Erschienen in: Annals of Data Science / Ausgabe 4/2018
Print ISSN: 2198-5804
Elektronische ISSN: 2198-5812
DOI: https://doi.org/10.1007/s40745-018-0153-4

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