%0 Journal Article
%T Cokriging for spatial functional data
%+ Laboratoire de MicrobiologiE de Géochimie et d'Ecologie Marines (LMGEM)
%A Nerini, David
%A Monestiez, Pascal
%A Manté, Claude
%< avec comité de lecture
%Z MIO:10-093
%@ 0047-259X
%J Journal of Multivariate Analysis
%I Elsevier
%V 101
%N 2
%P 409-418
%8 2010-02
%D 2010
%R 10.1016/j.jmva.2009.03.005
%K Functional data analysis
%K RKHS
%K Functional linear model
%K Coregionalization
%K Cokriging
%K Legendre polynomials
%Z Sciences of the Universe [physics]/Ocean, Atmosphere
%Z Mathematics [math]/Statistics [math.ST]
%Z Statistics [stat]/Statistics Theory [stat.TH]Journal articles
%X 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.
%G English
%L hal-00743881
%U https://hal.science/hal-00743881
%~ CNRS
%~ UNIV-AMU
%~ GIP-BE
%~ LMGEM