Marshall-Olkin Extended Generalized Exponential Distribution: Properties, Inference and Application to Traffic Data

  •  Oseghale O. Innocent    
  •  Ayoola J. Femi    
  •  Oluwole Adegoke Nuga    
  •  Ogunde A. Adebisi    


This paper aims to develop a three-parameter distribution called the Marshall–Olkin Extended Generalized Exponential (MOEGE ) distribution, which can be used in analyzing both reliability and survival data. Some statistical properties of the new distribution have been studied, which include, moments, incomplete moments, Renyl entropy, stochastic ordering, order statistics, and the moment generating function. The MOEGE  distribution has submodels such as the Marshall–Olkin Extended Exponential (MOEE) , the Generalized Exponential (GE), and the Exponential (E)  distribution. The maximum likelihood estimation technique is used to obtain the parameters estimate of the MOEGE  distribution, also, we constructed a 95% asymptotic confidence interval for the parameters. The performances of the estimators have been studied using Monte Carlo simulation, and finally, to demonstrate the applicability of the MOEGE  distribution, a traffic data set has been used.

This work is licensed under a Creative Commons Attribution 4.0 License.
  • ISSN(Print): 1927-7032
  • ISSN(Online): 1927-7040
  • Started: 2012
  • Frequency: bimonthly

Journal Metrics

  • h-index (December 2021): 20
  • i10-index (December 2021): 51
  • h5-index (December 2021): N/A
  • h5-median(December 2021): N/A

( The data was calculated based on Google Scholar Citations. Click Here to Learn More. )