Volume 17, Issue 2 (12-2018)                   JIRSS 2018, 17(2): 165-179 | Back to browse issues page

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Omidi M, Mohammadzadeh M. Spatial Interpolation Using Copula for non-Gaussian Modeling of Rainfall Data. JIRSS. 2018; 17 (2) :165-179
URL: http://jirss.irstat.ir/article-1-462-en.html
Phd Department of Mathematics‎, ‎Ilam University‎, ‎Ilam‎, ‎Iran
Abstract:   (860 Views)

‎One of the most useful tools for handling multivariate distributions of dependent variables in terms of their marginal distribution is a copula function‎.

‎The copula families capture a fair amount of attention due to their applicability and flexibility in describing the non-Gaussian spatial dependent data‎.

‎The particular properties of the spatial copula are rarely seen in all the known copula families‎. ‎In the present paper‎, ‎based on‎

‎the weighted geometric mean of two Max-id copulas family‎, ‎the spatial copula function is provided‎. ‎Afterwards‎, ‎the proposed copula‎

‎along with the Bees algorithm is used to explore the spatial dependency and to interpolate the rainfall data in Iran's Khuzestan province‎.

Full-Text [PDF 696 kb]   (21 Downloads)    
Type of Study: Original Paper | Subject: 60Exx: Distribution theory
Received: 2017/09/4 | Accepted: 2018/02/5 | Published: 2018/02/5

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