Multivariate functional random fields: prediction and optimal sampling
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Mostra el registre complet de l'elementcomunitat-uji-handle:10234/9
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INVESTIGACIONAquest recurs és restringit
https://doi.org/10.1007/s00477-016-1266-y |
Metadades
Títol
Multivariate functional random fields: prediction and optimal samplingData de publicació
2017Editor
Springer VerlagISSN
1436-3259; 1436-3240Cita bibliogràfica
BOHORQUEZ, M.; GIRALDO, R.; MATEU, J. Multivariate functional random fields: prediction and optimal sampling. Stochastic Environmental Research and Risk Assessment, 2016, p. 1-18Tipus de document
info:eu-repo/semantics/articleVersió de l'editorial
http://link.springer.com/article/10.1007/s00477-016-1266-yVersió
info:eu-repo/semantics/publishedVersionParaules clau / Matèries
Resum
This paper develops spatial prediction of a functional variable at unsampled sites, using functional covariates, that is, we present a functional cokriging method. We show that through the representation of each ... [+]
This paper develops spatial prediction of a functional variable at unsampled sites, using functional covariates, that is, we present a functional cokriging method. We show that through the representation of each function in terms of its empirical functional principal components, the functional cokriging only depends on the auto-covariance and cross-covariance of the associated scores vectors, which are scalar random fields. In addition, we propose the methodology to find optimal sampling designs in this context. The proposal is applied to the network of air quality in México city. [-]
Publicat a
Stochastic Environmental Research and Risk Assessment, 2016, vol. 31, n. 1Drets d'accés
© Springer-Verlag Berlin Heidelberg 2016
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http://rightsstatements.org/vocab/InC/1.0/
info:eu-repo/semantics/restrictedAccess
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