Ordinary kriging for function-valued spatial data

Clicks: 206
ID: 265931
2010
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Abstract
In various scientific fields properties are represented by functions varying over space. In this paper, we present a methodology to make spatial predictions at non-data locations when the data values are functions. In particular, we propose both an estimator of the spatial correlation and a functional kriging predictor. We adapt an optimization criterion used in multivariable spatial prediction in order to estimate the kriging parameters. The curves are pre-processed by a non-parametric fitting, where the smoothing parameters are chosen by cross-validation. The approach is illustrated by analyzing real data based on soil penetration resistances.
Reference Key
giraldo2010environmentalordinary Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors R. Giraldo;P. Delicado;J. Mateu;R. Giraldo;P. Delicado;J. Mateu;
Journal environmental and ecological statistics
Year 2010
DOI
doi:10.1007/s10651-010-0143-y
URL
https://dx.doi.org/10.1007/s10651-010-0143-y
Keywords
Ecology medicine physics Health Sciences statistics for engineering computer science chemistry and earth sciences statistics for life sciences math. appl. in environmental science theoretical ecology/statistics

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