The Extended Odd Family of Probability Distributions with Practice to a Submodel

Hassan Bakouch, Christophe Chesneau, Muhammad Nauman Khan


In this paper, we study a new family of distributions extending the recent odd family of distributions. The main feature of this extension is to increase the
exibility of the odd family of distribution by introducing a new tuning parameter, allowing the construction of new statistical models. Some math- ematical results are obtained, including moments, generating function and order statistics. Estimation of the family parameters by the maximum likelihood method is discussed. A multivariate extension of the family is hinted. We illustrate the potentiality of our extended odd family of distributions with applications to three practical data sets.


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