Spatial Interpolation Using Copula for non-Gaussian Modeling of Rainfall Data

‎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 Iranchr('39')s Khuzestan province‎.