An improved spectral turning-bands algorithm for simulating stationary vector Gaussian random fields
Author
dc.contributor.author
Emery, Xavier
Author
dc.contributor.author
Arroyo, Daisy
Author
dc.contributor.author
Porcu, Emilio
Admission date
dc.date.accessioned
2017-03-01T20:22:41Z
Available date
dc.date.available
2017-03-01T20:22:41Z
Publication date
dc.date.issued
2016
Cita de ítem
dc.identifier.citation
Stochastic Environmental Research and Risk Assessment. Volumen: 30 Número: 7 Páginas: 1863-1873
es_ES
Identifier
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1436-3240
Identifier
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https://repositorio.uchile.cl/handle/2250/142869
Abstract
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We propose a spectral turning-bands approach for the simulation of second-order stationary vector Gaussian random fields. The approach improves existing spectral methods through coupling with importance sampling techniques. A notable insight is that one can simulate any vector random field whose direct and cross-covariance functions are continuous and absolutely integrable, provided that one knows the analytical expression of their spectral densities, without the need for these spectral densities to have a bounded support. The simulation algorithm is computationally faster than circulant-embedding techniques, lends itself to parallel computing and has a low memory storage requirement. Numerical examples with varied spatial correlation structures are presented to demonstrate the accuracy and versatility of the proposal.