English

An exceptional max-stable process fully parameterized by its extremal coefficients

Statistics Theory 2015-04-15 v1 Statistics Theory

Abstract

The extremal coefficient function (ECF) of a max-stable process XX on some index set TT assigns to each finite subset ATA\subset T the effective number of independent random variables among the collection {Xt}tA\{X_t\}_{t\in A}. We introduce the class of Tawn-Molchanov processes that is in a 1:1 correspondence with the class of ECFs, thus also proving a complete characterization of the ECF in terms of negative definiteness. The corresponding Tawn-Molchanov process turns out to be exceptional among all max-stable processes sharing the same ECF in that its dependency set is maximal w.r.t. inclusion. This entails sharp lower bounds for the finite dimensional distributions of arbitrary max-stable processes in terms of its ECF. A spectral representation of the Tawn-Molchanov process and stochastic continuity are discussed. We also show how to build new valid ECFs from given ECFs by means of Bernstein functions.

Keywords

Cite

@article{arxiv.1504.03459,
  title  = {An exceptional max-stable process fully parameterized by its extremal coefficients},
  author = {Kirstin Strokorb and Martin Schlather},
  journal= {arXiv preprint arXiv:1504.03459},
  year   = {2015}
}

Comments

Published at http://dx.doi.org/10.3150/13-BEJ567 in the Bernoulli (http://isi.cbs.nl/bernoulli/) by the International Statistical Institute/Bernoulli Society (http://isi.cbs.nl/BS/bshome.htm)

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