A universal kriging approach for spatial functional data
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http://dx.doi.org/10.1007/s00477-013-0691-4 |
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Title
A universal kriging approach for spatial functional dataDate
2013-02Publisher
SpringerBibliographic citation
CABALLERO, William; GIRALDO, Ramón; MATEU, Jorge. A universal kriging approach for spatial functional data. Stochastic Environmental Research and Risk Assessment, 2013, 27.7: 1553-1563.Type
info:eu-repo/semantics/articlePublisher version
http://link.springer.com/article/10.1007/s00477-013-0691-4Version
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Abstract
In a wide range of scientific fields the outputs coming from certain measurements often come in form of curves. In this paper we give a solution to the problem of spatial prediction of non-stationary functional data. ... [+]
In a wide range of scientific fields the outputs coming from certain measurements often come in form of curves. In this paper we give a solution to the problem of spatial prediction of non-stationary functional data. We propose a new predictor by extending the classical universal kriging predictor for univariate data to the context of functional data. Using an approach similar to that used in univariate geostatistics we obtain a matrix system for estimating the weights of each functional variable on the prediction. The proposed methodology is validated by analyzing a real dataset corresponding to temperature curves obtained in several weather stations of Canada. [-]
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Stochastic Environmental Research and Risk Assessment October 2013, Volume 27, Issue 7Rights
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