RT - Journal Article T1 - Analysis of Spatial Data with Chi-Square Copula JF - JSS YR - 2020 JO - JSS VO - 13 IS - 2 UR - http://jss.irstat.ir/article-1-589-en.html SP - 363 EP - 384 K1 - ‎Chi-Square Copula‎ K1 - ‎Composite Pairwise Likelihood‎ K1 - ‎Isotropic Spatial Random Field‎ K1 - ‎Spatial Interpolation. AB - 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. LA eng UL http://jss.irstat.ir/article-1-589-en.html M3 10.29252/jss.13.2.363 ER -