The Exponentiated-Gompertz-Marshall-Olkin-G Family of Distributions: Properties and Applications

  • Oarabille Lekhane University of Botswana
  • Broderick Oluyede
  • Lesego Gabaitiri
  • Onkabetse V. Mabikwa
DOI: https://doi.org/10.19139/soic-2310-5070-1905
Keywords: Exponentiated-G, Gompertz-G, Marshall-Olkin-G, Maximum Likelihood Estimation, Simulations

Abstract

A new generalized family of distributions referred to as Exponentiated-Gompertz-Marshall-Olkin-G (EGom-MO-G) distribution is introduced. The distribution can be expressed as an infinite linear combination of the exponentiated-G family of distributions. Some mathematical properties are derived and studied. Several estimation techniques including maximum likelihood estimation, Cram\'{e}r-von Mises, least squares estimation, weighted least squares, Anderson-Darling and right-tail Anderson-Darling methods are compared. A special case of the new family of distributions is adopted for application to two real data sets and compared to some existing models. Results revealed that the new family of distributions is superior than compared models.
Published
2025-02-24
How to Cite
Lekhane, O., Oluyede, B., Gabaitiri, L., & Mabikwa, O. V. (2025). The Exponentiated-Gompertz-Marshall-Olkin-G Family of Distributions: Properties and Applications. Statistics, Optimization & Information Computing. https://doi.org/10.19139/soic-2310-5070-1905
Issue
Online First
Section
Research Articles
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