Nonseparable, Space-Time Covariance Functions with Dynamical Compact Supports

Emilio Porcu, Moreno Bevilacqua, Marc G. Genton

Research output: Contribution to journalArticlepeer-review

12 Scopus citations


The paper provides new classes of nonseparable space-time covariance functions with spatial (or temporal) margin belonging to the Generalized Wendland class of compactly supported covariance functions. An interesting feature of our covariances, from the computational viewpoint, is that the compact support is a decreasing function of the temporal (spatial) lag. We provide conditions for the validity of the proposed class, and analyze the problem of differentiability at the origin for the temporal (spatial) margin. A simulation study explores the finite sample properties and the computational burden associated with the maximum likelihood estimation of the covariance parameters. Finally, we use the proposed covariance models on Irish wind speed data and compare them with Gneiting-Mat´ern models in terms of fitting, prediction efficiency and computational burden. Necessary and sufficient conditions together with other results on dynamically varying compact supports are provided in the Online Supplement to this paper.
Original languageEnglish (US)
JournalStatistica Sinica
StatePublished - 2020

Bibliographical note

KAUST Repository Item: Exported on 2020-10-01
Acknowledgements: The research work conducted by Moreno Bevilacqua was supported in part by FONDECYT grant 1160280 Chile. Emilio Porcu was partly supported by FONDECYT 1130647 Chile. The work of Marc G. Genton was supported by King Abdullah University of Science and Technology (KAUST).


Dive into the research topics of 'Nonseparable, Space-Time Covariance Functions with Dynamical Compact Supports'. Together they form a unique fingerprint.

Cite this