Abstract
Pickands constants play a crucial role in the asymptotic theory of Gaussian processes. They are commonly defined as the limits of a sequence of expectations involving fractional Brownian motions and, as such, their exact value is often unknown. Recently, Dieker and Yakir (Bernoulli, 20(3), 1600–1619, 2014) derived a novel representation of Pickands constant as a simple expected value that does not involve a limit operation. In this paper we show that the notion of Pickands constants and their corresponding Dieker–Yakir representations can be extended to a large class of stochastic processes, including general Gaussian and Lévy processes. We furthermore develop a link to extreme value theory and show that Pickands-type constants coincide with certain constants arising in the study of max-stable processes with mixed moving maxima representations.
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Acknowledgments
We are grateful to three anonymous referees, Thomas Mikosch and Ilya Molchanov for numerous important suggestions. In particular, the new M3 representation (??) was suggested by one of the referees. Financial support by the Swiss National Science Foundation grants 200021-166274 (EH) and 161297 (SE), and partial support by NCN Grant No 2015/17/B/ST1/01102 (2016-2019) (KD) is gratefully acknowledged.
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Dȩbicki, K., Engelke, S. & Hashorva, E. Generalized Pickands constants and stationary max-stable processes. Extremes 20, 493–517 (2017). https://doi.org/10.1007/s10687-017-0289-1
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DOI: https://doi.org/10.1007/s10687-017-0289-1
Keywords
- Brown–Resnick process
- Fractional Brownian motion
- Gaussian process
- Generalized Pickands constant
- Lévy process
- Max-stable process
- Mixed moving maxima representation