基于Copula的非高斯降水数据空间插值建模

IF 0.1 Q4 STATISTICS & PROBABILITY
M. Omidi, M. Mohammadzadeh
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引用次数: 0

摘要

。根据因变量的边际分布来处理因变量的多变量分布的最有用的工具之一是联结函数。由于它们在描述非高斯空间相关数据方面的适用性和可操作性,联结族获得了相当多的关注。空间联结体的特殊性质在所有已知的联结体科中都很少见。本文基于两个Max-id copula族的加权几何平均值,给出了空间copula函数。然后,将提出的copula与蜜蜂算法一起用于探索空间依赖性,并对伊朗胡齐斯坦省的降雨数据进行插值。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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 (cid:13)exibil-ity 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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CiteScore
1.50
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