Inference for heavy tailed stationary time series based on sliding blocks

@article{Bucher2017InferenceFH,
  title={Inference for heavy tailed stationary time series based on sliding blocks},
  author={Axel Bucher and J. Segers},
  journal={Electronic Journal of Statistics},
  year={2017},
  volume={12},
  pages={1098-1125}
}
The block maxima method in extreme value theory consists of fitting an extreme value distribution to a sample of block maxima extracted from a time series. Traditionally, the maxima are taken over disjoint blocks of observations. Alternatively, the blocks can be chosen to slide through the observation period, yielding a larger number of overlapping blocks. Inference based on sliding blocks is found to be more efficient than inference based on disjoint blocks. The asymptotic variance of the… Expand

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