Analysis of estimation methods for the extremal index


Many datasets present time-dependent variation and short-term clustering
within extreme values. The extremal index is a primary measure to evaluate clustering
of high values in a stationary sequence. Estimation procedures are based on the choice
of a threshold and/or a declustering parameter or a block size. Here we revise several
dierent methods and compare them through simulation. In particular, we will see
that a recent declustering methodology may be useful for the popular runs estimator
and for a new estimator that works under the validation of a local dependence condition. An application to real data is also presented.

DOI Code: 10.1285/i20705948v11n1p296

Keywords: declustering; extreme value theory; local dependence conditions; stationary sequences

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