Gamma Generalized Power Lomax: A Novel Distribution in Modelling Covid-19 Data

  • A. A. Ogunde Department of Statistics, University of Ibadan, Oyo State.
  • O. I. Oseghale Department of Statistics, Joseph Ayo Babalola University, Ikeji-Arakeji, Osun State
  • S. A. Phillips Department of Statistics, Federal School of Statistics, Ibadan, Oyo State
  • D. O. Omosigho Deparment of Mathematics and Statistics, Federal Polytechnic Ado, Ado-Ekiti, Ekiti
DOI: https://doi.org/10.6084/zenodo.8269763
Keywords: Moments, generating function, covid-19 data, incomplete moments, maximum likelihood function

Abstract

In this study, we developed a flexible form of Power Lomax distribution called Gamma Power Lomax distribution. This distribution was obtained by combining the Power Lomax and Gamma distributions to generates a novel life-time distribution with three parameters. Different structural characteristics of the new distribution have been determined and analysed which includes moments, moment generating function, order statistics, and incomplete moments. Distinct plots depict the behaviour of the density and the distribution function. The maximum likelihood estimation method was applied to estimate the distribution parameters. The practicability of the stated distribution is proven by Covid-19 data set. The objective of this study is to establish an optimum statistical model considering current covid-19 pandemic.

Published
2023-08-20
How to Cite
Ogunde, A. A., Oseghale, O. I., Phillips, S. A., & Omosigho, D. O. (2023). Gamma Generalized Power Lomax: A Novel Distribution in Modelling Covid-19 Data. International Journal of Mathematical Sciences and Optimization: Theory and Applications, 9(1), 138 - 147. https://doi.org/10.6084/zenodo.8269763
Issue
Vol 9 No 1 (2023)
Section
Articles

Copyright (c) 2023 A. A. Ogunde, O. I. Oseghale, S. A. Phillips, D. O. Omosigho

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This work is licensed under a Creative Commons Attribution 4.0 International License.

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.