Families of spatio-temporal stationary covariance models

By Chunsheng Ma. 2003

132 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Environmental Engineering

View Paper: https://www.semanticscholar.org/paper/f3b68ba559d54883947cf1309c0456ecfa27cc9d

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Citations in the corpus

Modelling spatio-temporal data: A new variogram and covariance structure proposal (2007, background): “The proof of this sufficient condition can be obtained applying Pólya (1949) theorem for radial functions and the corresponding extension to R , which can be found in Gneiting (2001).”
Statistical methods for regular monitoring data (2005, background): “…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 of these models adapted to S2r × R?”
New classes of covariance and spectral density functions for spatio-temporal modelling (2008, background): “It is worth citating Jones and Zhang (1997), Cressie and Huang (1999), Christakos (2000), De Cesare et al. (2001), Gneiting (2002), Ma (2003) , Stein (2005) and Ferna ´ndez-Casal (2003).”
Geostatistical Space-Time Models, Stationarity, Separability, and Full Symmetry (2007, background): “Similar constructions of stationary space-time covariance functions have been reported by Cox and Isham (1988) and Ma (2003b), among others.”
Space–Time Covariance Functions (2005, background): “The proof is similar to that of theorem 2 of Ma (2003).”
Some covariance models based on normal scale mixtures (2011, methodology): “…principles (Ma (2008)), such as spectral methods (Stein (2005a)), multiplicative mixture models (Ma (2002)), additive models (Ma (2005c)), turning bands upgrade (Kolovos et al. (2004)), derivatives and integrals (Ma (2005b)), and Gneiting’s (2002) approach, see also Stein (2005c) and Ma (2003).”
Separable approximations of space‐time covariance matrices (2007, background): “Recent efforts have been allocated to develop new parametric classes of nonseparable space-time covariance models; see, for example, Cressie and Huang (1999), Gneiting (2002b), Ma (2003) , and Stein (2005), among others.”
Recent developments on the construction of spatio-temporal covariance models (2008, methodology): “The cosine transform method is an effective approach to derive spatio-temporal covariances and can be constructed as follows; see also Ma (2003a) .”
Methods for generating non-separable spatiotemporal covariance models with potential environmental applications (2004, methodology): “Certain extensions of the model (4) were proposed by Ma [29].”