Multivariate functional random fields: prediction and optimal sampling
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Show full item recordcomunitat-uji-handle:10234/9
comunitat-uji-handle2:10234/7037
comunitat-uji-handle3:10234/8635
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https://doi.org/10.1007/s00477-016-1266-y |
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Title
Multivariate functional random fields: prediction and optimal samplingDate
2017Publisher
Springer VerlagISSN
1436-3259; 1436-3240Bibliographic citation
BOHORQUEZ, M.; GIRALDO, R.; MATEU, J. Multivariate functional random fields: prediction and optimal sampling. Stochastic Environmental Research and Risk Assessment, 2016, p. 1-18Type
info:eu-repo/semantics/articlePublisher version
http://link.springer.com/article/10.1007/s00477-016-1266-yVersion
info:eu-repo/semantics/publishedVersionAbstract
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. [-]
Is part of
Stochastic Environmental Research and Risk Assessment, 2016, vol. 31, n. 1Rights
© 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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