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A class of valid Matérn cross-covariance functions for multivariate spatio-temporal random fields

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  • Ip, Ryan H.L.
  • Li, W.K.

Abstract

We extend a current result in the literature by introducing a parametric family of matrix-valued cross-covariance functions, which would help describe multivariate space–time dependence structures for any number of variables. All the direct and cross-covariance functions belong to the Matérn class. The smoothness, space–time separability and scale parameters are allowed to be different for each variable.

Suggested Citation

  • Ip, Ryan H.L. & Li, W.K., 2017. "A class of valid Matérn cross-covariance functions for multivariate spatio-temporal random fields," Statistics & Probability Letters, Elsevier, vol. 130(C), pages 115-119.
    • Handle: RePEc:eee:stapro:v:130:y:2017:i:c:p:115-119
    DOI: 10.1016/j.spl.2017.07.019
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    References listed on IDEAS

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    5. Li, Bo & Zhang, Hao, 2011. "An approach to modeling asymmetric multivariate spatial covariance structures," Journal of Multivariate Analysis, Elsevier, vol. 102(10), pages 1445-1453, November.
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    9. Moreno Bevilacqua & Carlo Gaetan & Jorge Mateu & Emilio Porcu, 2012. "Estimating Space and Space-Time Covariance Functions for Large Data Sets: A Weighted Composite Likelihood Approach," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 107(497), pages 268-280, March.
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