Non-separable models are receiving a lot of attention, since they are more flexible to handle empirical covariances showed up in applications. Most of the papers which develop space-time covariance functions end with a case study which tries to prove the adequacy of the proposed class of models to a specified data set. In literature it is not customary to follow the opposite path; in other words, starting from the data set, the problem is to look for the class of space-time covariance functions which is appropriate for data under study. This is the aim of this paper and it will be followed by utilizing several theoretical results found in the literature.
Selecting space-time covariance functions for modeling environmental data
CAPPELLO, CLAUDIA;DE IACO, Sandra;POSA, Donato;PALMA, Monica
2015-01-01
Abstract
Non-separable models are receiving a lot of attention, since they are more flexible to handle empirical covariances showed up in applications. Most of the papers which develop space-time covariance functions end with a case study which tries to prove the adequacy of the proposed class of models to a specified data set. In literature it is not customary to follow the opposite path; in other words, starting from the data set, the problem is to look for the class of space-time covariance functions which is appropriate for data under study. This is the aim of this paper and it will be followed by utilizing several theoretical results found in the literature.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
