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Unit Modified Burr-III Distribution: Estimation, Characterizations and Validation Test

Unit Modified Burr-III Distribution: Estimation, Characterizations and Validation Test In this paper, a new three-parameter unit probability distribution is proposed. The new model is a generalization of Burr III distribution, and it is more flexible than some existing well-known distribution due to its different shapes of the hazard function and probability density functions. The mathematical properties of this distribution are presented, including moments, reliability measures, mean residual life, and characterizations, and we also propose a modified Chi squared goodness-of-fit test based on Nikulin–Rao–Robson statistic Y2 in the presence of complete and censored data. The parameters related to the proposed distribution are estimated using well-known estimation methods. A numerical simulations study is conducted for reinforcement of the results. In the end, we considered two real datasets to illustrate the applicability of the proposed model. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Annals of Data Science Springer Journals

Unit Modified Burr-III Distribution: Estimation, Characterizations and Validation Test

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References (38)

Publisher
Springer Journals
Copyright
Copyright © Springer-Verlag GmbH Germany, part of Springer Nature 2020
ISSN
2198-5804
eISSN
2198-5812
DOI
10.1007/s40745-020-00298-6
Publisher site
See Article on Publisher Site

Abstract

In this paper, a new three-parameter unit probability distribution is proposed. The new model is a generalization of Burr III distribution, and it is more flexible than some existing well-known distribution due to its different shapes of the hazard function and probability density functions. The mathematical properties of this distribution are presented, including moments, reliability measures, mean residual life, and characterizations, and we also propose a modified Chi squared goodness-of-fit test based on Nikulin–Rao–Robson statistic Y2 in the presence of complete and censored data. The parameters related to the proposed distribution are estimated using well-known estimation methods. A numerical simulations study is conducted for reinforcement of the results. In the end, we considered two real datasets to illustrate the applicability of the proposed model.

Journal

Annals of Data ScienceSpringer Journals

Published: Apr 1, 2023

Keywords: Burr III distribution; Moments; Estimation; Characterization; Goodness-of-fit test

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