Bivariate Weibull-G Family Based on Copula Function: Properties, Bayesian and non-Bayesian Estimation and Applications

This paper aims to obtain a new flexible bivariate generalized family of distributions based on FGM copula, which is called Weibull-G family. Some its statistical properties are studied as marginal distributions, product moments, and moment generating functions. dependence measures Kendall’s tau median regression model discussed. After introducing the general class, four special sub models introduced by taking baseline Pareto, inverted Topp-Leone, exponential, Rayleigh distributions. Maximum likelihood Bayesian approaches used estimate unknown parameters. Further, percentile bootstrap confidence interval bootstrap-t estimated for model’s A Monte-Carlo simulation study carried out maximum estimators. Finally, we illustrate importance proposed using two real data sets in medical field.