In this paper close parallels between Geostatistics-based models and spatial autoregression models are examined and the possible role of the inverse correlation function of a Gaussian Random Field in an interpolation context is discussed. Theoretical results suggest here that a space-time interpolator can be achieved by means of a spatiotemporal Gaussian Markov Random Field (ST-GMRF). The predictive ability of this model is demonstrated by a simulation study
Prediction of Spatio-Temporal Gaussian fields using the Inverse Correlation Function
FONTANELLA, Lara;IPPOLITI, Luigi;
2005-01-01
Abstract
In this paper close parallels between Geostatistics-based models and spatial autoregression models are examined and the possible role of the inverse correlation function of a Gaussian Random Field in an interpolation context is discussed. Theoretical results suggest here that a space-time interpolator can be achieved by means of a spatiotemporal Gaussian Markov Random Field (ST-GMRF). The predictive ability of this model is demonstrated by a simulation studyFile in questo prodotto:
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