International Journal of Data Science and Analysis

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On the Flexibility of Topp Leone Exponentiated Inverse Exponential Distribution

Received: 01 May 2020    Accepted: 10 June 2020    Published: 17 July 2020
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Abstract

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.

DOI 10.11648/j.ijdsa.20200603.12
Published in International Journal of Data Science and Analysis (Volume 6, Issue 3, June 2020)

This article belongs to the Special Issue Data Science

Page(s) 83-89
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This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

Distribution, Inverse Exponential, Ordinary Moment, Parameter, Quantile Function

References
[1] G. S. Mudholkar and D. K. Srivastava, 1993, Exponentiated Weibull family for analyzing bathtub failure data, IEEE Transactions on Reliability, 42, 299-302.
[2] R. C. Gupta, P. L. Gupta and R. D. Gupta, 1998, Modeling failure time data by Lehmann alternatives. Communications in Statistics-Theory and Methods, 27, 887-904.
[3] R. C. Gupta and D. Kundu, 2001, Exponentiated exponential family; an alternative to gamma and Weibull, Biometrical Journal, 43, 117-130.
[4] A. S. Hassan and M. Abd-Allah, 2018, Exponentiated Weibull-Lomax Distribution: Properties and Estimation. Journal of Data Science, 277-298.
[5] R. Jan, T. R. Jan and P. B. Ahmad, 2018, Exponentiated Inverse Power Lindley Distribution and its Applications. arXivpreprintarXiv: 1808.07410.
[6] A. S. Hassan and M. A. Abdelghafar, 2017, Exponentiated Lomax geometric distribution: Properties and applications. Pakistan Journal of Statistics and Operation Research, 13, 3, 545-566.
[7] A. H. El-Bassiouny, M. El-Damcese, A. Mustafa and M. S. Eliwa, 2017, Exponentiated generalized Weibull-Gompertz distribution with application in survival analysis. Journal of Statistical Application and Probability, 6, 7-16.
[8] A. Z. Keller and A. R. Kamath, 1982, Reliability analysis of CNC Machine Tools. Reliability Engineering, 3, 449-473.
[9] P. E. Oguntunde and A. O. Adejumo, 2015, The transmuted inverse exponential distribution. International Journal of Advanced Statistics and Probability, 3, 1, 1-7. doi: 10.14419/ijasp.v3i1.3684.
[10] P. E. Oguntunde, A. O. Adejumo and E. A Owoloko, 2017, Application of Kumaraswamy inverse exponential distribution to real-life time data. International Journal of Applied Mathematics and Statistics, 56, 5, 34-47.
[11] P. E. Oguntunde, A. O. Adejumo and E. A. Owoloko, 2017, July 5-7, On the flexibility of the transmuted inverse exponential distribution. Lecture Notes on engineering and computer science: Proceeding of the World Congresson Engineering (123-126). London, UK.
[12] S. Ibrahim, S. I. Doguwa, I. Audu and H. M. Jibril, 2020, On the Topp Leone exponentiated-G Family of Distributions: Properties and Applications. Asian Journal of Probability and Statistics, 7, 1, 1-15.
[13] J. P. Klein and M. L. Moeschberger, 2003, Survival analysis: technique for censored and truncated data (2nd Edition), Springer, New York, USA, 535 Pages, ISBN978–0-387-21645-4.
[14] E. Umeh and A. Ibenegbu, 2019, A Two-Parameter Pranav Distribution with Properties and Its Application; Journal of Biostatistics and Epidemiology, 5, 1, 74–90.
Author Information
  • Department of Statistics, Faculty of Physical Sciences, Ahmadu Bello University, Zaria, Nigeria

  • Department of Statistics, Faculty of Physical Sciences, Ahmadu Bello University, Zaria, Nigeria

  • Department of Statistics, School of Physical Sciences, Federal University of Technology, Minna, Nigeria

  • Department of Mathematics, Faculty of Physical Sciences, Ahmadu Bello University, Zaria, Nigeria

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  • APA Style

    Sule Ibrahim, Sani Ibrahim Doguwa, Audu Isah, Haruna Muhammad Jibril. (2020). On the Flexibility of Topp Leone Exponentiated Inverse Exponential Distribution. International Journal of Data Science and Analysis, 6(3), 83-89. https://doi.org/10.11648/j.ijdsa.20200603.12

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    ACS Style

    Sule Ibrahim; Sani Ibrahim Doguwa; Audu Isah; Haruna Muhammad Jibril. On the Flexibility of Topp Leone Exponentiated Inverse Exponential Distribution. Int. J. Data Sci. Anal. 2020, 6(3), 83-89. doi: 10.11648/j.ijdsa.20200603.12

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    AMA Style

    Sule Ibrahim, Sani Ibrahim Doguwa, Audu Isah, Haruna Muhammad Jibril. On the Flexibility of Topp Leone Exponentiated Inverse Exponential Distribution. Int J Data Sci Anal. 2020;6(3):83-89. doi: 10.11648/j.ijdsa.20200603.12

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  • @article{10.11648/j.ijdsa.20200603.12,
      author = {Sule Ibrahim and Sani Ibrahim Doguwa and Audu Isah and Haruna Muhammad Jibril},
      title = {On the Flexibility of Topp Leone Exponentiated Inverse Exponential Distribution},
      journal = {International Journal of Data Science and Analysis},
      volume = {6},
      number = {3},
      pages = {83-89},
      doi = {10.11648/j.ijdsa.20200603.12},
      url = {https://doi.org/10.11648/j.ijdsa.20200603.12},
      eprint = {https://download.sciencepg.com/pdf/10.11648.j.ijdsa.20200603.12},
      abstract = {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.},
     year = {2020}
    }
    

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    T1  - On the Flexibility of Topp Leone Exponentiated Inverse Exponential Distribution
    AU  - Sule Ibrahim
    AU  - Sani Ibrahim Doguwa
    AU  - Audu Isah
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    DO  - 10.11648/j.ijdsa.20200603.12
    T2  - International Journal of Data Science and Analysis
    JF  - International Journal of Data Science and Analysis
    JO  - International Journal of Data Science and Analysis
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    EP  - 89
    PB  - Science Publishing Group
    SN  - 2575-1891
    UR  - https://doi.org/10.11648/j.ijdsa.20200603.12
    AB  - 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.
    VL  - 6
    IS  - 3
    ER  - 

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