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On a continuous spectral algorithm for simulating non-stationary Gaussian random fields

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This paper presents an algorithm for simulating Gaussian random fields with zero mean and non-stationary covariance functions. The simulated field is obtained as a weighted sum of cosine waves with… Click to show full abstract

This paper presents an algorithm for simulating Gaussian random fields with zero mean and non-stationary covariance functions. The simulated field is obtained as a weighted sum of cosine waves with random frequencies and random phases, with weights that depend on the location-specific spectral density associated with the target non-stationary covariance. The applicability and accuracy of the algorithm are illustrated through synthetic examples, in which scalar and vector random fields with non-stationary Gaussian, exponential, Matérn or compactly-supported covariance models are simulated.

Keywords: random fields; stationary gaussian; algorithm simulating; non stationary; gaussian random

Journal Title: Stochastic Environmental Research and Risk Assessment
Year Published: 2017

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