| Authors: | Claudia Cappello, Sandra De Iaco, Donato Posa | ||||
| Title: | covatest: An R Package for Selecting a Class of Space-Time Covariance Functions | ||||
| Abstract: | Although a very rich list of classes of space-time covariance functions exists, specific tools for selecting the appropriate class for a given data set are needed. Thus, the main topic of this paper is to present the new R package, covatest, which can be used for testing some characteristics of a covariance function, such as symmetry, separability and type of non-separability, as well as for testing the adequacy of some classes of space-time covariance models. These last aspects can be relevant for choosing a suitable class of covariance models. The proposed results have been applied to an environmental case study. | ||||
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Page views:: 3207. Submitted: 2018-02-11. Published: 2020-06-30. |
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| Paper: |
covatest: An R Package for Selecting a Class of Space-Time Covariance Functions
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| DOI: |
10.18637/jss.v094.i01
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This work is licensed under the licenses Paper: Creative Commons Attribution 3.0 Unported License Code: GNU General Public License (at least one of version 2 or version 3) or a GPL-compatible license. |