Recent advances to model anisotropic space–time data
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http://dx.doi.org/10.1007/s10260-007-0056-6 |
Metadatos
Título
Recent advances to model anisotropic space–time dataFecha de publicación
2008-05Editor
Springer-VerlagISSN
1618-2510Tipo de documento
info:eu-repo/semantics/articleVersión de la editorial
http://link.springer.com/article/10.1007/s10260-007-0056-6Versión
info:eu-repo/semantics/publishedVersionPalabras clave / Materias
Resumen
Building new and flexible classes of nonseparable spatio-temporal covariances and variograms has resulted a key point of research in the last years. The goal of this paper is to present an up-to-date overview of recent ... [+]
Building new and flexible classes of nonseparable spatio-temporal covariances and variograms has resulted a key point of research in the last years. The goal of this paper is to present an up-to-date overview of recent spatio-temporal covariance models taking into account the problem of spatial anisotropy. The resulting structures are proved to have certain interesting mathematical properties, together with a considerable applicability. In particular, we focus on the problem of modelling anisotropy through isotropy within components. We present the Bernstein class, and a generalisation of Gneiting’s approach (2002a) to obtain new classes of space–time covariance functions which are spatially anisotropic. We also discuss some methods for building covariance functions that attain negative values. We finally present several differentiation and integration operators acting on particular space–time covariance classes. [-]
Publicado en
Statistical Methods and Applications, 17, 2Derechos de acceso
© Springer-Verlag 2007
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