Exponentiated Weibull Power Series Distributions and its Applications

Abstract

In this paper we introduce the exponentiated Weibull power series (EWPS) class of distributions which is obtained by compounding exponentiated Weibull and power series distributions, where the compounding procedure follows same way that was previously carried out by Roman et al. (2010) and Cancho et al. (2011) in introducing the complementary exponential-geometric (CEG) and the two-parameter Poisson-exponential (PE) lifetime distributions, respectively. This distribution contains several lifetime models such as: exponentiated weibull-geometric (EWG), exponentiated weibull-binomial (EWB), exponentiated weibull-poisson (EWP), exponentiated weibull-logarithmic (EWL) distributions as a special case. The hazard rate function of the EWPS distribution can be increasing, decreasing, bathtub-shaped and unimodal failure rate among others. We obtain several properties of the EWPS distribution such as its probability density function, its reliability and failure rate functions, quantiles and moments. The maximum likelihood estimation procedure via a EM-algorithm is presented in this paper. Sub-models of the EWPS distribution are studied in details. In the end, Applications to two real data sets are given to show the flexibility and potentiality of the EWPS distribution.