A New Class of Generalized Burr III Distribution for Lifetime Data
International Journal of Statistical Distributions and Applications
Volume 4, Issue 1, March 2018, Pages: 6-21
Received: Jan. 4, 2018; Accepted: Feb. 24, 2018; Published: Mar. 28, 2018
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Authors
Olobatuyi Kehinde, Department of Statistics, Federal University of Agriculture, Abeokuta, Nigeria
Asiribo Osebi, Department of Statistics, Federal University of Agriculture, Abeokuta, Nigeria
Dawodu Ganiyu, Department of Statistics, Federal University of Agriculture, Abeokuta, Nigeria
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Abstract
For the first time, the Generalized Gamma Burr III (GGBIII) is introduced as an important model for problems in several areas such as actuarial sciences, meteorology, economics, finance, environmental studies, reliability, and censored data in survival analysis. A review of some existing gamma families have been presented. It was found that the distributions cannot exhibit complicated shapes such as unimodal and modified unimodal shapes which are very common in medical field. The Generalized Gamma Burr III (GGBIII) distribution which includes the family of Zografos and Balakrishnan as special cases is proposed and studied. It is expressed as the linear combination of Burr III distribution and it has a tractable properties. Some mathematical properties of the new distribution including hazard, survival, reverse hazard rate function, moments, moments generating function, mean and median deviations, distribution of the order statistics are presented. Maximum likelihood estimation technique is used to estimate the model parameters and applications to real datasets in order to illustrate the usefulness of the model are presented. Examples and applications as well as comparisons of the GGBIII to the existing Gamma-G families are given.
Keywords
Burr III Distribution, Generalized-Gamma Distribution, Censored Data, Maximum Likelihood Estimation
To cite this article
Olobatuyi Kehinde, Asiribo Osebi, Dawodu Ganiyu, A New Class of Generalized Burr III Distribution for Lifetime Data, International Journal of Statistical Distributions and Applications. Vol. 4, No. 1, 2018, pp. 6-21. doi: 10.11648/j.ijsd.20180401.12
Copyright
Copyright © 2018 Authors retain the copyright of this article.
This article is an open access article distributed under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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