Likelihood-Based Inference for Max-Stable Processes

  title={Likelihood-Based Inference for Max-Stable Processes},
  author={Simone A. Padoan and Mathieu Ribatet and S. A. Sisson},
  journal={Journal of the American Statistical Association},
  pages={263 - 277}
The last decade has seen max-stable processes emerge as a common tool for the statistical modeling of spatial extremes. However, their application is complicated due to the unavailability of the multivariate density function, and so likelihood-based methods remain far from providing a complete and flexible framework for inference. In this article we develop inferentially practical, likelihood-based methods for fitting max-stable processes derived from a composite-likelihood approach. The… 
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