Ordinary kriging for function-valued spatial data

By Ramón Giraldo, Pedro Delicado, Jorge Mateu. Environmental and Ecological Statistics, 2011

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A universal kriging approach for spatial functional data (2013, methodology): “Difference = (SSE for OKFD) - (SSE for UKFD). there are small differences between the two methods in terms of SSE values.”
A penalized regression model for spatial functional data with application to the analysis of the production of waste in Venice province (2016, methodology): “Starting from the pioneering work of Goulard and Voltz (1993), kriging prediction methods for stationary spatial functional data are developed in Delicado et al. (2010), Nerini et al. (2010) and Giraldo et al. (2011).”
A Universal Kriging predictor for spatially dependent functional data of a Hilbert Space (2013, background): “…a relatively small body of literature has been produced on this topic: indeed, theoretical results in this direction have been recently derived (Giraldo et al. (2008b, 2011); Delicado et al. (2010); Giraldo et al. (2010a); Monestiez and Ner-ini (2008); Nerini et al. (2010)) moving from the…”