International Journal of Data Science and Analysis
Volume 6, Issue 3, June 2020, Pages: 83-89
Received: May 1, 2020;
Accepted: Jun. 10, 2020;
Published: Jul. 17, 2020
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Sule Ibrahim, Department of Statistics, Faculty of Physical Sciences, Ahmadu Bello University, Zaria, Nigeria
Sani Ibrahim Doguwa, Department of Statistics, Faculty of Physical Sciences, Ahmadu Bello University, Zaria, Nigeria
Audu Isah, Department of Statistics, School of Physical Sciences, Federal University of Technology, Minna, Nigeria
Haruna Muhammad Jibril, Department of Mathematics, Faculty of Physical Sciences, Ahmadu Bello University, Zaria, Nigeria
In this paper, we introduced a new continuous probability distribution called the Topp Leone exponentiated inverse exponential distribution with three parameters. We studied the nature of proposed distribution with the help of its mathematical and statistical properties such as quantile function, ordinary moments, moment generating function, survival function and hazard function. The probability density function of order statistic for this distribution was also obtained. We performed classical estimation of parameters by using the technique of maximum likelihood estimate. The proposed model was applied to two real-life datasets. The first data set has to do with patients with cancer of tongue with aneuploidy DNA profile and the second data set has to do with patients who were diagnosed with hypertension and received at least one treatment related to hypertension. The results showed that the new distribution provided better fit than other distributions presented. As such, it can be categorically said that the Topp Leone exponentiated inverse exponential distribution is good distribution in modeling survival data.
Sani Ibrahim Doguwa,
Haruna Muhammad Jibril,
On the Flexibility of Topp Leone Exponentiated Inverse Exponential Distribution, International Journal of Data Science and Analysis. Special Issue: Data Science.
Vol. 6, No. 3,
2020, pp. 83-89.
Copyright © 2020 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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