Cokriging for spatial functional data
This work proposes to generalize the method of kriging when data are spatially sampled curves. A spatial functional linear model is constructed including spatial dependencies between curves. Under some regularity conditions of the curves, an ordinary kriging system is established in the infinite dim...
Published in: | Journal of Multivariate Analysis |
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Main Authors: | , , |
Other Authors: | , |
Format: | Article in Journal/Newspaper |
Language: | English |
Published: |
HAL CCSD
2010
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Subjects: | |
Online Access: | https://hal.science/hal-00743881 https://doi.org/10.1016/j.jmva.2009.03.005 |
Summary: | This work proposes to generalize the method of kriging when data are spatially sampled curves. A spatial functional linear model is constructed including spatial dependencies between curves. Under some regularity conditions of the curves, an ordinary kriging system is established in the infinite dimensional case. From a practical point-of-view, the decomposition of the curves into a functional basis boils down the problem of kriging in infinite dimension to a standard cokriging on basis coefficients. The methodological developments are illustrated with temperature profiles sampled with dives of elephant seals in the Antarctic Ocean. The projection of sampled profiles into a Legendre polynomial basis is performed with a regularization procedure based on spline smoothing which uses the variance of the sampling devices in order to estimate coefficients by quadrature. |
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