Weighted composite likelihood-based tests for space-time separability of covariance functions
| Autor: | A Zini, Moreno Bevilacqua, Emilio Porcu, Jorge Mateu, H. Zhang |
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| Přispěvatelé: | Bevilacqua, M, Mateu, J, Porcu, E, Zhang, H, Zini, A |
| Jazyk: | angličtina |
| Rok vydání: | 2010 |
| Předmět: |
Statistics and Probability
Score test Space-time covariance functions Mathematical optimization Covariance function Covariance mapping Hurst effect Space-time covariance function Covariance Theoretical Computer Science Estimation of covariance matrices Computational Theory and Mathematics Space-time separability Full symmetry Likelihood-ratio test SECS-S/01 - STATISTICA Law of total covariance Applied mathematics Weighted composite likelihood Statistics Probability and Uncertainty Fractal dimension Mathematics Parametric statistics |
| Popis: | Testing for separability of space-time covariance functions is of great interest in the analysis of space-time data. In this paper we work in a parametric framework and consider the case when the parameter identifying the case of separability of the associated space-time covariance lies on the boundary of the parametric space. This situation is frequently encountered in space-time geostatistics. It is known that classical methods such as likelihood ratio test may fail in this case. We present two tests based on weighted composite likelihood estimates and the bootstrap method, and evaluate their performance through an extensive simulation study as well as an application to Irish wind speeds. The tests are performed with respect to a new class of covariance functions, which presents some desirable mathematical features and has margins of the Generalized Cauchy type. We also apply the test on a element of the Gneiting class, obtaining concordant results. © 2009 Springer Science+Business Media, LLC. |
| Databáze: | OpenAIRE |
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