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Bayesian Model Averahing in Inverse Gaussian Regression Analysis
Afshin Fallah , Zahra Rahimian Azad
Abstract:   (254 Views)
This paper considers the Bayesian model averaging of inverse Gaussian regression models for regression analysis in situations that the response observations are positive and right-skewed. The computational challenges related to computing the essential quantities for executing of this methodology and their dominating ways are discussed. Providing closed form expressions for the interested posterior quantities by considering suitable prior distributions is an attractive aspect of the proposed methodology. The proposed approach has been evaluated via a simulation study and its applicability is expressed by using a real example related to the seismic studies. 
Keywords: Bayesian Model Averaging, Regression, Inverse Gaussian Distribution, Predictive Distribution.
Full-Text [PDF 7097 kb]   (3 Downloads)    
Type of Study: Research | Subject: General
Received: 2020/03/18 | Accepted: 2021/09/1
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مجله علوم آماری – نشریه علمی پژوهشی انجمن آمار ایران Journal of Statistical Sciences
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