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Omidi M, Mohammadzadeh M. Spatial Interpolation Using Copula for non-Gaussian Modeling of Rainfall Data. JIRSS. 2017; 17 (1)
URL: http://jirss.irstat.ir/article-1-462-en.html
URL: http://jirss.irstat.ir/article-1-462-en.html
Phd Department of Mathematics, Ilam University, Ilam, Iran
Abstract: (451 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 captured 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.
Type of Study: Original Paper |
Subject:
60Exx: Distribution theory
Received: 2017/09/4 | Accepted: 2018/02/5 | Published: 2018/02/5
Received: 2017/09/4 | Accepted: 2018/02/5 | Published: 2018/02/5
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