Simulating space-time random fields with nonseparable Gneiting-type covariance functions
Author
dc.contributor.author
Allard, Denis
Author
dc.contributor.author
Emery, Xavier
Author
dc.contributor.author
Lacaux, Céline
Author
dc.contributor.author
Lantuéjoul, Christian
Admission date
dc.date.accessioned
2020-08-22T01:45:16Z
Available date
dc.date.available
2020-08-22T01:45:16Z
Publication date
dc.date.issued
2020
Cita de ítem
dc.identifier.citation
Statistics and Computing. Vol. 30, pp.1479–1495: (2020)
es_ES
Identifier
dc.identifier.other
10.1007/s11222-020-09956-4
Identifier
dc.identifier.uri
https://repositorio.uchile.cl/handle/2250/176512
Abstract
dc.description.abstract
Two algorithms are proposed to simulate space-time Gaussian random fields with a covariance function belonging to an extended Gneiting class, the definition of which depends on a completely monotone function associated with the spatial structure and a conditionally negative definite function associated with the temporal structure. In both cases, the simulated random field is constructed as a weighted sum of cosine waves, with a Gaussian spatial frequency vector and a uniform phase. The difference lies in the way to handle the temporal component. The first algorithm relies on a spectral decomposition in order to simulate a temporal frequency conditional upon the spatial one, while in the second algorithm the temporal frequency is replaced by an intrinsic random field whose variogram is proportional to the conditionally negative definite function associated with the temporal structure. Both algorithms are scalable as their computational cost is proportional to the number of space-time locations that may be irregular in space and time. They are illustrated and validated through synthetic examples.
es_ES
Patrocinador
dc.description.sponsorship
RESSTE network - Applied Mathematics and Informatics division of INRA
National Agency for Research and Development of Chile
CONICYT PIA AFB180004