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Abstract:
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Based on a recent paper, we propose to model spatial extremes using factor copula models. These models assume the presence of a common factor affecting the joint dependence of all measurements. When the common factor is exponentially distributed, the resulting copula is asymptotically equivalent to the H\"usler-Reiss copula; therefore, the so-called exponential factor model is suitable to model tail dependence. Under the assumption of local stationarity, the exponential factor model is used to model extreme measurements over high thresholds. Inference is performed using a censored local likelihood. Performance is assessed using simulation experiments, and illustrated using a daily rainfall dataset.
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