Journal
STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT
Volume 30, Issue 7, Pages 1863-1873Publisher
SPRINGER
DOI: 10.1007/s00477-015-1151-0
Keywords
Matrix-valued covariance functions; Spectral density; Importance sampling; Matern covariance; Compactly supported covariance
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Funding
- Chilean Commission for Scientific and Technological Research [1130085, 3140568, 1130647]
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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.
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