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

Authors

  • Oarabille Lekhane 1Department of Statistics, University of Botswana, Botswana; 2Department of Mathematics and Statistical Sciences, Botswana International University of Science and Technology, Botswana
  • Broderick Oluyede Department of Mathematics and Statistical Sciences, Botswana International University of Science and Technology, Botswana
  • Lesego Gabaitiri Department of Mathematics and Statistical Sciences, Botswana International University of Science and Technology, Botswana
  • Onkabetse V. Mabikwa Department of Mathematics and Statistical Sciences, Botswana International University of Science and Technology, Botswana

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.

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Published

2025-02-24

Issue

Vol. 13 No. 5 (2025)

Section

Research Articles

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How to Cite

The Exponentiated-Gompertz-Marshall-Olkin-G Family of Distributions: Properties and Applications. (2025). Statistics, Optimization & Information Computing, 13(5), 1752-1788. https://doi.org/10.19139/soic-2310-5070-1905

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