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A class of non-Gaussian second order random fields

Sofia Åberg (Institutionen för matematiska vetenskaper, matematisk statistik) ; K. Podgorski
Extremes (1386-1999). Vol. 14 (2011), 2, p. 187-222.
[Artikel, refereegranskad vetenskaplig]

Non-Gaussian stochastic fields are introduced by means of integrals with respect to independently scattered stochastic measures distributed according to generalized Laplace laws. In particular, we discuss stationary second order random fields that, as opposed to their Gaussian counterpart, have a possibility of accounting for asymmetry and heavier tails. Additionally to this greater flexibility the models discussed continue to share most spectral properties with Gaussian processes. Their statistical distributions at crossing levels are computed numerically via the generalized Rice formula. The potential for stochastic modeling of real life phenomena that deviate from the Gaussian paradigm is exemplified by a stochastic field model with Matérn covariances.

Nyckelord: Laplace distribution, Spectral density, Covariance function, Stationary, second order processes, Rice formula, infinitely divisible processes

Denna post skapades 2011-05-24. Senast ändrad 2016-11-07.
CPL Pubid: 140990


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Institutioner (Chalmers)

Institutionen för matematiska vetenskaper, matematisk statistik (2005-2016)


Matematisk statistik

Chalmers infrastruktur