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A class of non-Gaussian second order random fields

In English

Författare

Summary, in English

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 Mat,rn covariances.

Publiceringsår

2011

Språk

Engelska

Sidor

187-222

Publikation/Tidskrift/Serie

Extremes

Volym

14

Issue

2

Dokumenttyp

Artikel i tidskrift

Förlag

Springer

Ämne

  • Probability Theory and Statistics

Nyckelord

  • Laplace distribution
  • Spectral density
  • Covariance function
  • Stationary
  • second order processes
  • Rice formula

Status

Published

ISBN/ISSN/Övrigt

  • ISSN: 1572-915X