Ordinary kriging for function-valued spatial data
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- Giraldo, R., Delicado, P. & Mateu, J. Environ Ecol Stat (2011) 18: 411. doi:10.1007/s10651-010-0143-y
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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.