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

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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.

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Acknowledgements

The authors are grateful to two anonymous reviewers for their constructive comments and acknowledge the support of the Chilean Commission for Scientific and Technological Research, through Projects CONICYT PIA Anillo ACT1407 and CONICYT/FONDECYT/POSTDOCTORADO/N°3140568.

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  1. Daisy Arroyo

    Present address: Department of Statistics, University of Concepción, Concepción, Chile

Authors and Affiliations

  1. Department of Mining Engineering, University of Chile, Santiago, Chile

    Xavier Emery & Daisy Arroyo

  2. Advanced Mining Technology Center, University of Chile, Santiago, Chile

    Xavier Emery & Daisy Arroyo

Authors
  1. Xavier Emery
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  2. Daisy Arroyo
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Correspondence to Xavier Emery.

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Emery, X., Arroyo, D. On a continuous spectral algorithm for simulating non-stationary Gaussian random fields. Stoch Environ Res Risk Assess 32, 905–919 (2018). https://doi.org/10.1007/s00477-017-1402-3

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