Multivariate functional random fields: prediction and optimal sampling

被引：0
作者：
M. Bohorquez
R. Giraldo
J. Mateu
机构：
[1] National University of Colombia,Department of Statistics
[2] Universitat Jaume I,Department of Mathematics
来源：
Stochastic Environmental Research and Risk Assessment | 2017年 / 31卷
关键词：
Functional data; Multivariate geostatistics; Optimal sampling;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
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.
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页码：53 / 70
页数：17
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