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JSRI 2020, 16(2): 559-569 Back to browse issues page
A Note on the Identifiability of General Bayesian Gaussian Models
Amirhossein Ghatari *1, Ashkan Shabbak2, Elham Tabrizi3
1- Amirkabir University of Technology , a.h.ghatari@aut.ac.ir
2- Statistical Research and Training Center
3- Kharazmi University
Abstract:   (640 Views)
The main aim of this paper is to investigate the identifiability of Bayesian Gaussian regression model. The model is extensively implemented in the various Bayesian modeling concepts such as model fitting and model selection approaches. In accordance with the outcomes, the Bayesian Gaussian model is identifiable when the model's design matrix is full rank.
Keywords: Bayesian statistics, design matrix, Gaussian model, identifiability, Posterior distribution.
Full-Text [PDF 198 kb]   (119 Downloads)    
Type of Study: Research | Subject: General
Received: 2021/08/7 | Accepted: 2021/11/30 | Published: 2022/03/8
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Ghatari A, Shabbak A, Tabrizi E. A Note on the Identifiability of General Bayesian Gaussian Models. JSRI. 2020; 16 (2) :559-569
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Volume 16, Issue 2 (3-2020) Back to browse issues page
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