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A Class of Bivariate Generalized Gompertz-Power Series Distributions
Rasool Roozegar , Ali Akbar Jafari
Abstract:   (816 Views)

In this paper, we introduce a family of bivariate generalized Gompertz-power series distributions. This new class of bivariate distributions contains several models such as: bivariate generalized Gompertz -geometric, -Poisson, - binomial, -logarithmic, -negative binomial and bivariate generalized exponental-power series distributions as special cases. We express the method of construction and derive different properties of the proposed class of distributions. The method of maximum likelihood and EM algorithm are used for estimating the model parameters. Finally, we illustrate the usefulness of the new distributions by means of application to real data sets.

Keywords: Bivariate generalized Gompertz distribution, EM algorithm, Maximum likelihood estimation, Power series class of distribution.
Full-Text [PDF 6837 kb]   (206 Downloads)    
Type of Study: Research | Subject: Theoritical Statistics
Received: 2016/01/31 | Accepted: 2016/12/19 | Published: 2017/06/22
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Roozegar R, Jafari A A. A Class of Bivariate Generalized Gompertz-Power Series Distributions. J. of Stat. Sci.. 2017; 11 (1)
URL: http://jss.irstat.ir/article-1-446-en.html
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مجله علوم آماری – نشریه علمی پژوهشی انجمن آمار ایران Journal of Statistical Sciences
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