The concepts of isotropy/anisotropy and separability/non-separability of a covariance function are strictly related. If a covariance function is separable, it cannot be isotropic or geometrically anisotropic, except for the Gaussian covariance function, which is the only model both separable and isotropic. In this paper, some interesting results concerning the Gaussian covariance model and its properties related to isotropy and separability are given, and moreover, some examples are provided. Finally, a discussion on asymmetric models, with Gaussian marginals, is furnished and the strictly positive definiteness condition is discussed.
On Some Characteristics of Gaussian Covariance Functions
De Iaco, Sandra
;Posa, Donato;Cappello, Claudia;Maggio, Sabrina
2021-01-01
Abstract
The concepts of isotropy/anisotropy and separability/non-separability of a covariance function are strictly related. If a covariance function is separable, it cannot be isotropic or geometrically anisotropic, except for the Gaussian covariance function, which is the only model both separable and isotropic. In this paper, some interesting results concerning the Gaussian covariance model and its properties related to isotropy and separability are given, and moreover, some examples are provided. Finally, a discussion on asymmetric models, with Gaussian marginals, is furnished and the strictly positive definiteness condition is discussed.| File | Dimensione | Formato | |
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Int Statistical Rev - 2020 - De Iaco - On Some Characteristics of Gaussian Covariance Functions.pdf
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