Estimating and modeling space–time correlation structures
By L. Cesare, Donald E. Myers, D. Posa. 2001
189 citations recorded by the source corpus.
Subfields: Economics and Econometrics, Environmental Engineering
View Paper: https://www.semanticscholar.org/paper/c472a21b99e78005c8cb29603c28e209638aa3d3
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Economics and Econometrics
- Chunsheng Ma
- S. De Iaco
- D. Posa
- Donald E. Myers
- Michael L. Stein
- Martin Schlather
- Tilmann Gneiting
- Marc G. Genton
In Environmental Engineering
- Chunsheng Ma
- S. De Iaco
- D. Posa
- Donald E. Myers
- Michael L. Stein
- Martin Schlather
- Tilmann Gneiting
- Emilio Porcu
Citations in the corpus
- Nonseparable Space-Time Covariance Models: Some Parametric Families (2002, methodology): “Under the convenient assumption of treating space and time separately, the factorized covariance (8) and the nested variogram ( 9 ) represent one of the first attempts to generate parametric families of space-time covariances and variograms.”
- Spatio-Temporal Covariance Functions Generated by Mixtures (2002, methodology): “where CSD CS(0; 0); CTD CT (0; 0): A closely related model is the product-sum model introduced by De Cesare, Myers, and Posa (2001a) with an environmental application in De Cesare, Myers, and Posa (2001b).”