Non-stationary Gaussian random fields on hypersurfaces: Sampling and strong error analysis

Fuente: arXiv
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Autores principales: Jansson, Erik, Lang, Annika, Pereira, Mike
Formato: Preprint
Publicado: 2024
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author Jansson, Erik
Lang, Annika
Pereira, Mike
author_facet Jansson, Erik
Lang, Annika
Pereira, Mike
contents A flexible model for non-stationary Gaussian random fields on hypersurfaces is introduced.The class of random fields on curves and surfaces is characterized by an amplitude spectral density of a second order elliptic differential operator.Sampling is done by a Galerkin--Chebyshev approximation based on the surface finite element method and Chebyshev polynomials. Strong error bounds are shown with convergence rates depending on the smoothness of the approximated random field. Numerical experiments that confirm the convergence rates are presented.
format Preprint
id arxiv_https___arxiv_org_abs_2406_08185
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Non-stationary Gaussian random fields on hypersurfaces: Sampling and strong error analysis
Jansson, Erik
Lang, Annika
Pereira, Mike
Numerical Analysis
Probability
60G60, 60H35, 60H15, 65C30, 60G15, 58J05, 41A10, 65N30, 65M60
A flexible model for non-stationary Gaussian random fields on hypersurfaces is introduced.The class of random fields on curves and surfaces is characterized by an amplitude spectral density of a second order elliptic differential operator.Sampling is done by a Galerkin--Chebyshev approximation based on the surface finite element method and Chebyshev polynomials. Strong error bounds are shown with convergence rates depending on the smoothness of the approximated random field. Numerical experiments that confirm the convergence rates are presented.
title Non-stationary Gaussian random fields on hypersurfaces: Sampling and strong error analysis
topic Numerical Analysis
Probability
60G60, 60H35, 60H15, 65C30, 60G15, 58J05, 41A10, 65N30, 65M60
url https://arxiv.org/abs/2406.08185