Nonseparable Space-Time Covariance Models: Some Parametric Families

153 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Space–Time Covariance Functions (2005, background): “Cressie and Huang (1999), de Iaco et al. (2001, 2002), and Gneiting (2002) have described approaches to generating nonseparable space–time covariance functions.”
Spatio-temporal variograms and covariance models (2005, methodology): “These basic properties allow us to derive many nonseparable spatio-temporal covariance functions via mixture methods (e.g. de Iaco et al. (2002) and Ma (2002), (2003a), (2003c)), where the mixing weights are constrained to be nonnegative.”
Recent developments on the construction of spatio-temporal covariance models (2008, background): “A more general form (see De Iaco et al. 2002 ; M a 2003a )i s”
Statistical methods for regular monitoring data (2005, background): “…that have been suggested in recent works such as Christakos (1992, 2000), Jones and Zhang (1997), Cressie and Huang (1999), Brown et al. (2000), de Iaco et al. (2001, 2002, 2003), Gneiting (2002), Hartfield and Gunst (2003), Ma (2003), Kolovos et al. (2004) and Stein (2005), or at least versions…”
Geostatistical modelling of air temperature in a mountainous region of Northern Spain (2007, methodology): “…variograms were modelled as the sum of an isotropic spherical variogram and a Gaussian variogram for the Z-axis, which constitutes a valid model (De Iaco et al., 2002): gðdÞ ¼ gsphericalðx; y; zÞ þ gGaussianðzÞ (5) Ordinary kriging was carried out calculating the sum variogram for each pair of…”