In this paper, we among functional data. A first strategy aims to classify curves spatially dependent and to obtain a spatio-functional model prototype for each cluster. It is based on a Dynamic Clustering Algorithm with on an optimization problem that minimizes the spatial variability among the curves in each cluster. A second one looks simultaneously for an optimal partition of spatial functional data set and a set of bivariate functional regression models associated to each cluster. These models take into account both the interactions among different functional variables and the spatial relations among the observations.
CITATION STYLE
Romano, E., & Verde, R. (2012). Clustering geostatistical functional data. In Studies in Theoretical and Applied Statistics, Selected Papers of the Statistical Societies (pp. 23–31). Springer International Publishing. https://doi.org/10.1007/978-3-642-21037-2_3
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