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:: Volume 1, Issue 2 (2-2008) ::
J. of Stat. Sci. 2008, 1(2): 121-137 Back to browse issues page
Bayesian Estimation for the Signal Parameters in a Gaussian Random Field
Mohammad Reza Farid Rohani , Khalil Shafiei Holighi
Abstract:   (17840 Views)
In recent years, some statisticians have studied the signal detection problem by using the random field theory. In this paper we have considered point estimation of the Gaussian scale space random field parameters in the Bayesian approach. Since the posterior distribution for the parameters of interest dose not have a closed form, we introduce the Markov Chain Monte Carlo (MCMC) algorithm to approximate the Bayesian estimations. We have also applied the proposed procedure to real fMRI data, collected by the Montreal Neurological Institute.
Keywords: Random Field, Scale Space Random Field, Radon-Nikodym Derivative, MCMC.
Full-Text [PDF 678 kb]   (3230 Downloads)    
Type of Study: Research | Subject: Statistical Inference
Received: 2011/07/4 | Accepted: 2013/08/13 | Published: 2020/02/18
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Farid Rohani M R, Shafiei Holighi K. Bayesian Estimation for the Signal Parameters in a Gaussian Random Field. J. of Stat. Sci.. 2008; 1 (2) :121-137
URL: http://jss.irstat.ir/article-1-8-en.html

Volume 1, Issue 2 (2-2008) Back to browse issues page
مجله علوم آماری – نشریه علمی پژوهشی انجمن آمار ایران Journal of Statistical Sciences
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