Beta Weighted Exponential Distribution: Theory and Application

  • Nofiu I. Badmus Department of Statistics, Yaba College of Technology, Lagos, Nigeria
  • Adebayo T. Bamiduro Department of Mathematical Sciences, Redeemer’s University, Ede, Nigeria
  • Monsuru A . Rauf-Animasaun Department of Statistics, Yaba College of Technology, Lagos, Nigeria
  • Akeem A. Akingbade Department of Statistics, Yaba College of Technology, Lagos, Nigeria

Abstract

[10] modified the idea of [2] in which they introduced a shape parameter to an exponential model to
obtain the weighted exponential distribution. In this article, we introduced two shape parameters to the existing weighted exponential distribution to develop the beta weighted exponential distribution using the logit of beta function by [12]. We studied the statistical properties of the new distribution. Parameter estimation was done by the method of maximum likelihood estimation with R software code. We then used a data set on survival times of guinea pigs injected with different amount of tubercle bacilli to compare properties of well-known distributions with those of
the new distribution. Our comparison showed the new distribution as the much more flexible and versatile.

Published
2018-04-18
How to Cite
Badmus, N. I., Bamiduro, A. T., Rauf-Animasaun, M. A. ., & Akingbade, A. A. (2018). Beta Weighted Exponential Distribution: Theory and Application. International Journal of Mathematical Sciences and Optimization: Theory and Applications, 2015, 55 - 66. Retrieved from http://ijmso.unilag.edu.ng/article/view/17
Issue
Vol 2015
Section
Articles

This is an Open Access article distributed under the terms of the Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, adaptation, and reproduction in any medium, provided that the original work is properly cited.