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
Department of Mathematics‎, ‎Ilam University‎, ‎Ilam‎, ‎Iran , omidi_280@yahoo.com
Abstract:   (4101 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.

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Type of Study: Original Paper | Subject: 60Exx: Distribution theory
Received: 2017/09/4 | Accepted: 2018/02/5 | Published: 2018/08/6

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