Electronic Journal of Statistics
- Electron. J. Statist.
- Volume 7 (2013), 2209-2240.
A Universal Kriging predictor for spatially dependent functional data of a Hilbert Space
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.
Electron. J. Statist., Volume 7 (2013), 2209-2240.
Received: October 2012
First available in Project Euclid: 19 September 2013
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Menafoglio, Alessandra; Secchi, Piercesare; Dalla Rosa, Matilde. A Universal Kriging predictor for spatially dependent functional data of a Hilbert Space. Electron. J. Statist. 7 (2013), 2209--2240. doi:10.1214/13-EJS843. https://projecteuclid.org/euclid.ejs/1379596770
- Simulation Study. In this supplement, the performance of Algorithms 10 and 11 is tested through an extended simulation study.