On the Three-Parameter Burr Type XII Distribution and its Application to Heavy Tailed Lifetime Data

Authors

  • Mahmoud K. Okasha Al-Azhar University - Gaza, Gaza - Palestine
  • Mariam Y Matter Al-Azhar University - Gaza, Gaza - Palestine

DOI:

https://doi.org/10.24297/jam.v10i4.1242

Keywords:

Bur type distributions, kernel density estimate, lifetime data, maximum likelihood estimation, truncated distributions.

Abstract

This paper identifies the characteristics of three-parameter Burr Type XII distribution and discusses its utility in survivorship applications. It addresses the problem of estimating the three-parameter Burr XII distribution and its doubly truncated version. The results are applied on a real dataset by fitting the distribution to the survival time of breast cancer patients in the Gaza Strip. These data are known to have a heavy tailed distribution since patients in this area received different protocols of treatments in different levels of hospitals locally and abroad. The findings indicated that the estimates of the parameters of the truncated distribution are more efficient than those obtained from the original distribution since the distribution is heavy tailed and involves many highly extreme observations.

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Author Biographies

Mahmoud K. Okasha, Al-Azhar University - Gaza, Gaza - Palestine

I am currently a full time Professor of Statistics at Al-Azhar University - Gaza; Graduate of the School of Probability and Statistics at the University of Sheffield, England (Ph. D. and M. Sc. degrees) and the Faculty of Economics and Political Sciences in Cairo University(B. Sc. degree); have long experience as a university lecturer. Former Dean of Planning & Development, Vice-Prisedent for Administrative & Financial Affiars, and for Planning & Quality Assurance. at  the AUG.

Mariam Y Matter, Al-Azhar University - Gaza, Gaza - Palestine

Department of Applied Statistics

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Published

2015-04-22

How to Cite

Okasha, M. K., & Matter, M. Y. (2015). On the Three-Parameter Burr Type XII Distribution and its Application to Heavy Tailed Lifetime Data. JOURNAL OF ADVANCES IN MATHEMATICS, 10(4), 3429–3442. https://doi.org/10.24297/jam.v10i4.1242

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Articles