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:: Volume 7, Issue 1 (9-2013) ::
J. of Stat. Sci. 2013, 7(1): 77-102 Back to browse issues page
Bayesian Regression Model with Finite Mixture Bivariate Poisson Response Variable
Afshin Fallah , Mahsa Nadifar , Ramin Kazemi
Abstract:   (8446 Views)
In this paper the regression analysis with finite mixture bivariate poisson response variable is investigated from the Bayesian point of view. It is shown that the posterior distribution cannot be written in a closed form due to the complexity of the likelihood function of bivariate Poisson distribution. Hence, the full conditional posterior distributions of the parameters are computed and the Gibbs algorithm is used to sampling from posterior distributions. A simulation study is performed in order to assess the proposed Bayesian model and its efficiency in estimation of the parameters is compared with their frequentist counterparts. Also, a real example presented to illustrate and assess the proposed Bayesian model. The results indicate to the more efficiency of the estimators resulted from Bayesian approach than estimators of frequentist approach at least for small sample sizes.
Keywords: Poisson regression, Mixture distribution, EM algorithm
Full-Text [PDF 520 kb]   (1810 Downloads)    
Type of Study: Applied | Subject: Applied Statistics
Received: 2013/08/25 | Accepted: 2013/11/21 | Published: 2013/11/21
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Fallah A, Nadifar M, Kazemi R. Bayesian Regression Model with Finite Mixture Bivariate Poisson Response Variable. J. of Stat. Sci.. 2013; 7 (1) :77-102
URL: http://jss.irstat.ir/article-1-230-en.html


Volume 7, Issue 1 (9-2013) Back to browse issues page
مجله علوم آماری – نشریه علمی پژوهشی انجمن آمار ایران Journal of Statistical Sciences
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