We employed the notion of mixture distributions to suggest a new one parameter continuous distribution for modeling real lifetime data called Ola Distribution. Its properties are explored including moments and related measures, moment generating function, reliability analysis functions, order statistics, Bonferroni and Lorenz curves, stochastic ordering, Re ́nyi entropy and mean deviations. The maximum likelihood method is adapted to estimate the parameter of the distribution. Applications to engineering and COVID- 19 data sets are presented to illustrate the usefulness of the suggested distribution. The applications showed that Ola distribution outperforms some competitive distributions and can be considered as a useful tool for modeling such real data.
Digital Object Identifier (DOI)
Al-Ta’ani, Ola and M. Gharaibeh, Mohammed
"Ola Distribution: A New One Parameter Model with Applications to Engineering and Covid-19 Data,"
Applied Mathematics & Information Sciences: Vol. 17:
2, Article 7.
Available at: https://digitalcommons.aaru.edu.jo/amis/vol17/iss2/7