In many environmental sciences, the available information concern several correlated variables observed at some locations of the domain of interest and over a certain period of time. In this context, multivariate spatial-temporal data might exhibit an spatial anisotropy and a temporal trend. Then appropriate modeling and prediction techniques for multivariate spatial-temporal data are necessary. In this paper, a case study with an anisotropic space-time coregionalization model is discussed. Some critical steps of the fitting procedure are highlighted
Space-time multivariate analysis based on anisotropic covariance models
DE IACO, Sandra;MAGGIO, Sabrina;PALMA, Monica;POSA, Donato
2011-01-01
Abstract
In many environmental sciences, the available information concern several correlated variables observed at some locations of the domain of interest and over a certain period of time. In this context, multivariate spatial-temporal data might exhibit an spatial anisotropy and a temporal trend. Then appropriate modeling and prediction techniques for multivariate spatial-temporal data are necessary. In this paper, a case study with an anisotropic space-time coregionalization model is discussed. Some critical steps of the fitting procedure are highlightedFile in questo prodotto:
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