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 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.
Year of publication: |
2010
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Authors: | Nerini, David ; Monestiez, Pascal ; Manté, Claude |
Published in: |
Journal of Multivariate Analysis. - Elsevier, ISSN 0047-259X. - Vol. 101.2010, 2, p. 409-418
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Publisher: |
Elsevier |
Keywords: | Functional data analysis RKHS Functional linear model Coregionalization Cokriging Legendre polynomials |
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