Hierarchical clustering of spatially correlated functional data
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Title
Hierarchical clustering of spatially correlated functional dataDate
2012-11Publisher
John Wiley & SonsBibliographic citation
Statistica Neerlandica, 66, 4, p. 403-421Type
info:eu-repo/semantics/articleVersion
info:eu-repo/semantics/submittedVersionSubject
Abstract
Classification problems of functional data arise naturally in many applications. Several
approaches have been considered for solving the problem of funding groups based on functional data. In this paper we are ... [+]
Classification problems of functional data arise naturally in many applications. Several
approaches have been considered for solving the problem of funding groups based on functional data. In this paper we are interested in detecting groups when the functional data
are spatially correlated. Our methodology allows to find spatially homogeneous groups
of sites when the observations at each sampling location consist of samples of random
functions. In univariable and multivariable geostatistics various methods of incorporating
spatial information into the clustering analysis have been considered. Here we extend these
methods to the functional context in order to fulfill the task of clustering spatially correlated curves. In our approach we initially use basis functions to smooth the observed data
and then we weight the dissimilarity matrix among curves by either the trace-variogram
or the multivariable variogram calculated with the coeficients of the basis functions. As
an illustration the methodology is applied to a real data set corresponding to average daily
temperatures measured at 35 Canadian weather stations. [-]
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