Environmental and Ecological Statistics

, Volume 18, Issue 3, pp 411–426 | Cite as

Ordinary kriging for function-valued spatial data

  • R. Giraldo
  • P. Delicado
  • J. MateuEmail author


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.


Cross-validation Functional data Non-parametric curve fitting Ordinary kriging Soil penetration resistance Trace-variogram 


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© Springer Science+Business Media, LLC 2010

Authors and Affiliations

  1. 1.Universitat Politècnica de CatalunyaBarcelonaSpain
  2. 2.Universidad Nacional de ColombiaBogotáColombia
  3. 3.Department of MathematicsUniversity Jaume ICastellónSpain

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