The Exponentiated Half-logistic Odd Burr III-G: Model, Properties and Applications | [Pakistan Journal of Statistics and Operation Research • 2022]

Author(s):

1. Broderick Oluyede: Department of Mathematics & Statistical Sciences, Faculty of Science, Botswana International University of Science & Technology, Palapye, Botswana.

2. Peter O. Peter: Department of Mathematics & Statistical Sciences, Faculty of Science, Botswana International University of Science & Technology, Palapye, Botswana.

3. Nkumbuludzi Ndwapi: Department of Mathematics & Statistical Sciences, Faculty of Science, Botswana International University of Science & Technology, Palapye, Botswana.

4. Huybrechts Bindele: Department of Mathematics & Statistics, University of South Alabama, USA

Abstract:

In this article, we develop and study in detail a new family of distributions called exponentiated half-logistic Odd Burr III-G (EHL-OBIII-G). Some of the mathematical and statistical properties for this new family of distributions such as the hazard function, quantile function, moments, probability weighted moments, Re´nyi entropy and stochastic orders are derived. The model parameters are estimated using the maximum likelihood estimation method. The usefulness of the proposed family of distributions is demonstrated via extensive simulation studies. Finally the proposed model and its special case is applied to real data sets to illustrate its best fit and flexibility. The model is compared to some of the existing non-nested models having equal number of parameters and from these results, the proposed model performed better than other fitted models.

Page(s): 33-57

DOI: 10.18187/pjsor.v18i1.3668

Published: Journal: Pakistan Journal of Statistics and Operation Research, Volume: 18, Issue: 1, Year: 2022

Keywords:

maximum likelihood estimation , Odd BurrIII distribution , Halflogistic distribution , Family of distributions

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