Maximum composite likelihood estimation for spatial extremes models of Brown–Resnick type with application to precipitation data
研究了布朗-雷斯尼克型空间极值模型的最大复合似然估计，证明了估计量的一致性和渐近正态性，并通过蒙特卡洛模拟和降水数据验证了方法。
Abstract In this study, we consider the maximum composite likelihood estimator for spatial extremes model class of Brown–Resnick type. The composite likelihood is constructed based on the weighted tail empirical process. It is shown that the proposed estimator is consistent and asymptotically normal under some regularity conditions fulfilled by the model class. We conduct Monte Carlo simulations to evaluate the estimator and apply it to the analysis of a precipitation data set.