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:: Volume 13, Issue 2 (2-2020) ::
J. of Stat. Sci. 2020, 13(2): 363-384 Back to browse issues page
Analysis of Spatial Data with Chi-Square Copula
Ronak Jamshidi *, Sedigheh Shams
Abstract:   (2430 Views)
In this paper‎, ‎a family of copula functions called chi-square copula family is used for modeling the dependency structure of stationary and isotropic spatial random fields‎. ‎The dependence structure of this copula is such that‎, ‎it generalizes the Gaussian copula and flexible for modeling for high-dimensional random vectors and unlike Gaussian copula it allows for modeling of tail asymmetric dependence structures‎. ‎Since the density function of chi-square copula in high dimension has computational complexity‎, ‎therefore to estimate its parameters‎, ‎a composite pairwise likelihood method is used in which only bivariate density functions are used‎. ‎The purpose of this paper is to investigate the properties of the chi-square copula family‎, ‎estimating its parameters with the composite pairwise likelihood and its application in spatial interpolation.
Keywords: ‎Chi-Square Copula‎, ‎Composite Pairwise Likelihood‎, ‎Isotropic Spatial Random Field‎, ‎Spatial Interpolation.
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Type of Study: Research | Subject: Spatial Statistics
Received: 2018/04/9 | Accepted: 2018/12/15 | Published: 2019/08/16
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Jamshidi R, Shams S. Analysis of Spatial Data with Chi-Square Copula. J. of Stat. Sci.. 2020; 13 (2) :363-384
URL: http://jss.irstat.ir/article-1-589-en.html

Volume 13, Issue 2 (2-2020) Back to browse issues page
مجله علوم آماری – نشریه علمی پژوهشی انجمن آمار ایران Journal of Statistical Sciences
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