Application of the Exponentiated Log-Logistic Weibull Distribution to Censored Data

Authors

  • Adeniyi F. Fagbamigbe Department of Epidemiology and Medical Statistics, College of Medicine, Faculty of Public Health, University of Ibadan, Nigeria
  • Gomolemo K. Basele Department of Mathematics and Statistical Sciences, Botswana International University of Science and Technology, Palapye, BW
  • Boikanyo Makubate Department of Mathematics and Statistical Sciences, Botswana International University of Science and Technology, Palapye, BW
  • Broderick O. Oluyede Department of Mathematical Sciences, Georgia Southern University, Statesboro, GA, 30460, USA

Keywords:

Generalized Distribution, Exponentiated log-logistic Distribution, Weibull Distribution, Survival Analysis.

Abstract

In a recent paper, a new model called the Exponentiated Log-Logistic Weibull (ELLoGW) distribution with applications to reliability, survival analysis and income data was proposed. In this study, we applied the recently developed ELLoGW model to a wide range of censored data. We found that the ELLoGW distribution is a very competitive model for describing censored observations in life-time reliability problems such as survival analysis. This work shows that in certain cases, the ELLoGW distribution performs better than other parametric model such as the Log-Logistic Weibull, Exponentiated Log-Logistic Exponential, Log-Logistic Exponential distributions and the non-nested Gamma-Dagum (GD).

Dimensions

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Published

2019-03-31

How to Cite

Application of the Exponentiated Log-Logistic Weibull Distribution to Censored Data. (2019). Journal of the Nigerian Society of Physical Sciences, 1(1), 12-19. https://doi.org/10.46481/jnsps.2019.4

Issue

Volume 1, Issue 1, February 2019

Section

Original Research
Copyright & Licensing

Copyright (c) 2019 Journal of the Nigerian Society of Physical Sciences

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How to Cite

Application of the Exponentiated Log-Logistic Weibull Distribution to Censored Data. (2019). Journal of the Nigerian Society of Physical Sciences, 1(1), 12-19. https://doi.org/10.46481/jnsps.2019.4