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Erschienen in:
2015 | OriginalPaper | Buchkapitel
A Depth Function for Geostatistical Functional Data
verfasst von : Antonio Balzanella, Romano Elvira
Erschienen in: Advances in Statistical Models for Data Analysis
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Abstract
In this paper we introduce a depth measure for geostatistical functional data. The aim is to provide a tool which allows to get a center-outward ordering of functional data recorded by sensors placed on a geographic area. Although the topic of ordering functional data has already been addressed in the literature, no proposal analyzes the case in which there is a spatial dependence among the curves. With this aim, we extend a well-known depth measure for functional data by introducing a new component in the measurement, which accounts for the spatial covariance. An application of the proposed method to a wide range of simulated cases shows its effectiveness in discovering a useful ordering of the spatially located curves.