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Title: Max-convolution processes with random shape indicator kernels Authors:  Pavel Krupskiy - Melbourne University (Australia) [presenting]
Raphael Huser - King Abdullah University of Science and Technology (Saudi Arabia)
Abstract: A new class of models is introduced for spatial data obtained from max-convolution processes based on indicator kernels with random shapes. We study the tail properties of this class of models and show that these are flexible models that can handle complex dependence structures. We discuss estimation methods for these models and apply them to analyze a wind data set.