Methods for generating non-separable spatiotemporal covariance models with potential environmental applications

By Alexander Kolovos, George Christakos, Dionissios T. Hristopulos, Marc L. Serre. 2004

146 citations recorded by the source corpus.

Subfields: Ecology, Environmental Engineering, Global and Planetary Change

View Paper: https://www.semanticscholar.org/paper/e40a1012902d6a0ecf337281d84246ed9f34fa56

How researchers see this paper

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

In Ecology

1. Martin Schlather
2. Michael L. Stein
3. Emilio Porcu
4. Simon Michael Papalexiou
5. F. Serinaldi
6. Chunsheng Ma
7. Marc G. Genton
8. Tatiyana V. Apanasovich

In Environmental Engineering

1. Martin Schlather
2. Emilio Porcu
3. Jorge Mateu
4. Chunsheng Ma
5. Michael L. Stein
6. Fuensanta Saura
7. Marc G. Genton
8. Simon Michael Papalexiou

In Global and Planetary Change

1. Martin Schlather
2. Emilio Porcu
3. Chunsheng Ma
4. F. Serinaldi
5. Jorge Mateu
6. Fuensanta Saura
7. Simon Michael Papalexiou
8. Michael L. Stein

Citations in the corpus

• 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?”
• 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).”
• Recent developments on the construction of spatio-temporal covariance models (2008, methodology): “See also Christakos and Hristopulos (1998) and Kolovos et al. (2004) for other models generated from stochastic partial differential equations.”
• New classes of covariance and spectral density functions for spatio-temporal modelling (2008, background): “In the nonstationary context, important contributions come from Christakos (2000), Fuentes and Smith (2001), Fuentes (2002), Christakos (2002) and Kolovos et al. (2004) .”
• Random Fields Simplified: Preserving Marginal Distributions, Correlations, and Intermittency, With Applications From Rainfall to Humidity (2020, background): “However, although nonseparable models are often physically more realistic, separable models of space‐time covariance functions are valuable in both physical and health applications (Kolovos et al., 2004).”