Marshall-Olkin Exponentiated Fréchet Distribution

In this paper, a new distribution called Marshall-Olkin Exponentiated Fréchet (MOEFr) is proposed. The goal to increase the flexibility of existing by including an extra shape parameter, resulting into more flexible that can provide better fit various data sets than baseline distribution. A generator method introduced Marshall and Olkin used develop Some properties such as hazard rate function, survival reversed cumulative odds quantile moments order statistics are derived. maximum likelihood estimation estimate model parameters. Monte Carlo simulation evaluate behavior estimators through average bias root mean squared error. fitted compared with some distributions (EFr), (MOFr), Beta Exponential (BEFr), (BFr) (Fr) distributions, on three sets, namely Bladder cancer, Carbone Wheaton River sets. Based goodness-of-fit information criteria values, it demonstrated provides for other considered in study.