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Cubic Transmuted Pareto Distribution

Cubic Transmuted Pareto Distribution In this article, we have proposed the cubic transmuted Pareto distribution, by using the cubic transmuted family of distributions introduced by Rahman et al. (in Pak J Stat Oper Res 14:451–469, 2018). We have explored the distribution in detail and statistical properties of the distribution have been studied. The parameter estimation for the distribution has been discussed and the performance of estimators is studied by conducting extensive simulation study. Finally, the cubic transmuted Pareto distribution has been fitted on two real datasets to investigate it’s applicability. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Annals of Data Science Springer Journals

Cubic Transmuted Pareto Distribution

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Publisher
Springer Journals
Copyright
Copyright © Springer-Verlag GmbH Germany, part of Springer Nature 2018
Subject
Business and Management; Business and Management, general; Statistics for Business/Economics/Mathematical Finance/Insurance; Computing Methodologies
ISSN
2198-5804
eISSN
2198-5812
DOI
10.1007/s40745-018-0178-8
Publisher site
See Article on Publisher Site

Abstract

In this article, we have proposed the cubic transmuted Pareto distribution, by using the cubic transmuted family of distributions introduced by Rahman et al. (in Pak J Stat Oper Res 14:451–469, 2018). We have explored the distribution in detail and statistical properties of the distribution have been studied. The parameter estimation for the distribution has been discussed and the performance of estimators is studied by conducting extensive simulation study. Finally, the cubic transmuted Pareto distribution has been fitted on two real datasets to investigate it’s applicability.

Journal

Annals of Data Science – Springer Journals

Published: Mar 29, 2020

References

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    Rahman, MM; Al-Zahrani, B; Shahbaz, MQ
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    Merovci, F; Puka, L
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    Owoloko, EA; Oguntunde, PE; Adejumo, AO
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    Shannon, CE
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    Zaindin, M; Sarhan, AM
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    Aryal, GR; Tsokos, CP
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    Granzotto, DCT; Louzada, F; Balakrishnan, N
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    Abdul-Moniem, IB; Seham, M
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    Andrews, DF; Herzberg, AM
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    Akinsete, A; Famoye, F; Lee, C
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    Mudholkar, GS; Huston, AD