:: Volume 13, Number 2 (3-2017) ::
JSRI 2017, 13(2): 155-180 Back to browse issues page
Bayesian Analysis of Censored Spatial Data Based on a Non-Gaussian Model
Vahid Tadayon *
Abstract:   (1814 Views)

Abstract: In this paper, we suggest using a skew Gaussian-log Gaussian model for the analysis of spatial censored data from a Bayesian point of view. This approach furnishes an extension of the skew log Gaussian model to accommodate to both skewness and heavy tails and also censored data. All of the characteristics mentioned are three pervasive features of spatial data.

We utilize data augmentation method and Markov chain Monte Carlo (MCMC) algorithms to do posterior calculations. The methodology is illustrated using simulated data, as well as applying it to a real data set.

Keywords: Censored data, data augmentation, non-Gaussian spatial models, outlier, unified skew Gaussian.
Full-Text [PDF 1165 kb]   (1213 Downloads)    
Type of Study: Research | Subject: General
Received: 2016/03/22 | Accepted: 2017/01/15 | Published: 2017/06/11




DOI: 10.18869/acadpub.jsri.13.2.155


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Volume 13, Number 2 (3-2017) Back to browse issues page