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Selecting space-time covariance functions for modeling environmental data

Authors: CAPPELLO, CLAUDIA; DE IACO, Sandra; POSA, Donato; PALMA, Monica;

Selecting space-time covariance functions for modeling environmental data

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.

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Italy
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Keywords

Positive and negative non-separability, non-separability index,

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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