Abstract
We consider a space-time random field on given as an integral of a kernel function with respect to a Lévy basis with a convolution equivalent Lévy measure. The field obeys causality in time and is thereby not continuous along the time axis. For a large class of such random fields we study the tail behaviour of certain functionals of the field. It turns out that the tail is asymptotically equivalent to the right tail of the underlying Lévy measure. Particular examples are the asymptotic probability that there is a time point and a rotation of a spatial object with fixed radius, in which the field exceeds the level x, and that there is a time interval and a rotation of a spatial object with fixed radius, in which the average of the field exceeds the level x.
Original language | English |
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Journal | Journal of Applied Probability |
Volume | 58 |
Issue number | 1 |
Pages (from-to) | 42-67 |
Number of pages | 26 |
ISSN | 0021-9002 |
DOIs | |
Publication status | Published - Mar 2021 |
Bibliographical note
Epub ahead of print. Published online: 25. Februar 2021Keywords
- Convolution equivalence
- Infinite divisibility
- Lévy-based modelling
- Asymptotic equivalence
- Sample paths for random fields