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:: Volume 11, Issue 2 (3-2018) ::
JSS 2018, 11(2): 297-317 Back to browse issues page
Bayesian Analysis of Skew Normal Mixture Regression
Afshin Fallah * , Ramin Kazemi , Hasan Khosravi
Abstract:   (4717 Views)
Regression analysis is done, traditionally, considering homogeneity and normality assumption for the response variable distribution. Whereas in many applications, observations indicate to a heterogeneous structure containing some sub-populations with skew-symmetric structure either due to heterogeneity, multimodality or skewness of the population or a combination of them. In this situations, one can use a mixture of skew-symmetric distributions to model the population. In this paper we considered the Bayesian approach of regression analysis under the assumption of heterogeneity of population and a skew-symmetric distribution for sub-populations, by using a mixture of skew normal distributions. We used a simulation study and a real world example to assess the proposed Bayesian methodology and to compare it with frequentist approach.
Keywords: Bayesian Regression Analysis, Mixture Distribution, Skewness, EM Algorithm, Gibbs Algorithm
Full-Text [PDF 223 kb]   (1226 Downloads)    
Type of Study: Applied | Subject: Statistical Inference
Received: 2018/11/16 | Accepted: 2018/11/16 | Published: 2018/11/16
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Fallah A, Kazemi R, Khosravi H. Bayesian Analysis of Skew Normal Mixture Regression. JSS 2018; 11 (2) :297-317
URL: http://jss.irstat.ir/article-1-639-en.html

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Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Volume 11, Issue 2 (3-2018) Back to browse issues page
مجله علوم آماری – نشریه علمی پژوهشی انجمن آمار ایران Journal of Statistical Sciences

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