Volume 17, Issue 40 (Mathematic- 2015)
2015, 17(40): 85-98 |
Back to browse issues page
Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:
Mahdianfard N, Mohammadzadeh M. Bayesian Melding of Deterministic Models and Kriging For Analysis of Spatially Correlated Data. Journal title 2015; 17 (40) :85-98
URL: http://jsci.khu.ac.ir/article-1-2157-en.html
URL: http://jsci.khu.ac.ir/article-1-2157-en.html
1- Department of Statistics, Tarbiat Modares University
Abstract: (5797 Views)
Linking between geographic information systems and decision making approach own the invention and development of spatial data melding methods. Data melding methods combine the data, to achieve a better result and their aim is, to detect the information available in the data set in order to enhance the ability of interpreting data and increase the accuracy of the data analysis. In this paper, Bayesian melding method has been studied for combination of measurements, outputs of deterministic models and kriging methods. By spatial Bayesian melding and kriging an attempted is made to spatial prediction of ozone data in Tehran and results are validated and compared using the mean square error criterion.
Send email to the article author
| Rights and permissions | |
 | This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. |
