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A class of non-Gaussian second order random fields

Publiceringsår: 2011
Språk: Engelska
Sidor: 187-222
Publikation/Tidskrift/Serie: Extremes
Volym: 14
Nummer: 2
Dokumenttyp: Artikel i tidskrift
Förlag: Kluwer


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.


  • Probability Theory and Statistics
  • Laplace distribution
  • Spectral density
  • Covariance function
  • Stationary
  • second order processes
  • Rice formula


  • ISSN: 1572-915X

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