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2013 A Universal Kriging predictor for spatially dependent functional data of a Hilbert Space
Alessandra Menafoglio, Piercesare Secchi, Matilde Dalla Rosa
Electron. J. Statist. 7: 2209-2240 (2013). DOI: 10.1214/13-EJS843

Abstract

We address the problem of predicting spatially dependent functional data belonging to a Hilbert space, with a Functional Data Analysis approach. Having defined new global measures of spatial variability for functional random processes, we derive a Universal Kriging predictor for functional data. Consistently with the new established theoretical results, we develop a two-step procedure for predicting georeferenced functional data: first model selection and estimation of the spatial mean (drift), then Universal Kriging prediction on the basis of the identified model. The proposed methodology is applied to daily mean temperatures curves recorded in the Maritimes Provinces of Canada.

Citation

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Alessandra Menafoglio. Piercesare Secchi. Matilde Dalla Rosa. "A Universal Kriging predictor for spatially dependent functional data of a Hilbert Space." Electron. J. Statist. 7 2209 - 2240, 2013. https://doi.org/10.1214/13-EJS843

Information

Received: 1 October 2012; Published: 2013
First available in Project Euclid: 19 September 2013

zbMATH: 1293.62120
MathSciNet: MR3108813
Digital Object Identifier: 10.1214/13-EJS843

Subjects:
Primary: 62H11
Secondary: 62M20, 62M30

Rights: Copyright © 2013 The Institute of Mathematical Statistics and the Bernoulli Society

JOURNAL ARTICLE
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