On Bivariate Exponentiated Extended Weibull Family of Distributions

In this paper, we introduce a new class of bivariate distributions called the bivariate exponentiated extended Weibull distributions. The model introduced here is of Marshall-Olkin type. This new class of bivariate distributions contains several bivariate lifetime models. Some mathematical properties of the new class of distributions are studied. We provide the joint and conditional density functions, the joint cumulative distribution function and the joint survival function. Special bivariate distributions are investigated in some detail. The maximum likelihood estimators are obtained using the EM algorithm. We illustrate the usefulness of the new class by means of application to two real data sets.Comment: arXiv admin note: text overlap with arXiv:1501.03528 by other author

Marshall Olkin exponential Gompertz distribution: Properties and applications

Generalizing distribution is an important area in probability theory. Many distributions are not suitable for modeling data, that are either symmetric or heavily skewed. In this paper, a new compound distribution termed as Marshall Olkin Exponential Gompertz (MOEGo) is introduced. Several essential statistical properties of MOEGo distribution were studied and investigated. The estimation of distribution parameters was performed using the maximum likelihood estimation method. Two real data (symmetric and right-skewed) were adopted to illustrate the flexibility of MOEGo distribution. This flexibility enables the use of MOEGo distribution in various application areas