A flexible class of non-separable cross-covariance functions for multivariate space–time data

Author:

Bourotte Marc,Allard Denis,Porcu Emilio

Funder

French National Institute for Agricultural Research (INRA)

Chilean Ministry of Education

Publisher

Elsevier BV

Subject

Management, Monitoring, Policy and Law,Computers in Earth Sciences,Statistics and Probability

Reference31 articles.

1. Cross-covariance functions for multivariate random fields based on latent dimensions;Apanasovich;Biometrika,2010

2. A valid Matérn class of cross-covariance functions for multivariate random fields with any number of components;Apanasovich;J. Amer. Statist. Assoc.,2012

3. Comparing composite likelihood methods based on pairs for spatial Gaussian random fields;Bevilacqua;Stat. Comput.,2015

4. Estimating space and space–time covariance functions for large data sets: a weighted composite likelihood approach;Bevilacqua;J. Amer. Statist. Assoc.,2012

5. Castruccio, S., Huser, R., Genton, M., 2015. High-order composite likelihood inference for max-stable distributions and processes. arXiv:1411.0086v3.

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