Non-stationary Gaussian random fields on hypersurfaces: Sampling and strong error analysis
Preprint, 2024

A flexible model for non-stationary Gaussian random fields on hypersurfaces is this http URL class of random fields on curves and surfaces is characterized by an amplitude spectral density of a second order elliptic differential this http URL 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.

Gaussian random fields

Chebyshev approximation

Gaussian processes

stochastic partial differential equations

non-stationary random fields

surface finite element method

Författare

Erik Jansson

Chalmers, Matematiska vetenskaper, Tillämpad matematik och statistik

Annika Lang

Chalmers, Matematiska vetenskaper, Tillämpad matematik och statistik

Mike Pereira

Chalmers, Elektroteknik, System- och reglerteknik

Efficienta approximeringsmetoder för stokastiska fält på mångfalder

Vetenskapsrådet (VR) (2020-04170), 2021-01-01 -- 2024-12-31.

Time-Evolving Stochastic Manifolds (StochMan)

Europeiska kommissionen (EU) (EC/HE/101088589), 2023-09-01 -- 2028-08-31.

Ämneskategorier

Matematik

Beräkningsmatematik

Geometri

Sannolikhetsteori och statistik

Matematisk analys

DOI

10.48550/arXiv.2406.08185

Mer information

Senast uppdaterat

2024-12-20