[Home ] [Archive]   [ فارسی ]  
:: Main :: About :: Current Issue :: Archive :: Search :: Submit :: Contact ::
:: Volume 12, Issue 1 (9-2018) ::
J. of Stat. Sci. 2018, 12(1): 189-208 Back to browse issues page
Spatial Prediction By Using Unilateral Autoregressive Models In Two-Dimensional Space
Azadeh Mojiri , Yadolla Waghei , Hamid Reza Nili Sani , Gholam Reza Mohtashami Borzadaran
Abstract:   (742 Views)

Prediction of spatial variability is one of the most important issues in the analysis of spatial data. So predictions are usually made by assuming that the data follow a spatial model. In General, the spatial models are the spatial autoregressive (SAR), the conditional autoregressive and the moving average models.

In this paper, we estimated parameter of SAR(2,1) model by using maximum likelihood and obtained formulas for predicting in SAR models, including the prediction within the data (interpolation) and outside the data (extrapolation). Finally, we evaluate the prediction methods by using image processing data.

Keywords: Spatial Data, Unilateral Spatial Autoregressive Model, Prediction, Interpolation, Extrapolation
Full-Text [PDF 340 kb]   (187 Downloads)    
Type of Study: Research | Subject: Spatial Statistics
Received: 2016/05/25 | Accepted: 2017/02/27 | Published: 2018/04/15
Send email to the article author

Add your comments about this article
Your username or Email:


XML   Persian Abstract   Print

Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:

Mojiri A, Waghei Y, Nili Sani H R, Mohtashami Borzadaran G R. Spatial Prediction By Using Unilateral Autoregressive Models In Two-Dimensional Space. J. of Stat. Sci.. 2018; 12 (1) :189-208
URL: http://jss.irstat.ir/article-1-475-en.html

Volume 12, Issue 1 (9-2018) Back to browse issues page
مجله علوم آماری – نشریه علمی پژوهشی انجمن آمار ایران Journal of Statistical Sciences
Persian site map - English site map - Created in 0.05 seconds with 31 queries by YEKTAWEB 3742