Pseudo-likelihood ratio tests for semipara- metric multivariate copula model selection

نویسندگان

  • Xiaohong CHEN
  • Yanqin FAN
چکیده

The authors propose pseudo-likelihood ratio tests for selecting semiparametric multivariate copula models in which the marginal distributions are unspecified, but the copula function is parameterized and can be misspecified. For the comparison of two models, the tests differ depending on whether the two copulas are generalized non-nested or generalized nested. For more than two models, the procedure is built on the reality check test of White (2000). Unlike the latter, however, the test statistic is automatically standardized for generalized non-nested models (with the benchmark) and ignores generalized nested models asymptotically. The authors illustrate their approach with American insurance claim data. Tests du rapport des pseudo-vraisemblances pour la sélection de modèles de copules multivariés semiparamétriques Résumé : Les auteurs proposent l’emploi de tests du rapport des pseudo-vraisemblances pour la sélection de modèles de copules multivariés semiparamétriques dans lesquels les marges ne sont pas précisées et la copule paramétrique peut éventuellement être mal spécifiée. La forme du test permettant de comparer deux modèles varie selon que les copules sous-jacentes sont embôıtées ou non dans un sens large. La procédure permettant de comparer plusieurs modèles à la fois s’inspire du test de réalisme de White (2000). À la différence de ce dernier, cependant, la statistique du test est automatiquement standardisée (par rapport à un étalon) pour les modèles non-embôıtés et fait fi, asymptotiquement, des modèles embôıtés. Les auteurs illustrent leur approche à l’aide de données américaines de sinistres en assurance.

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تاریخ انتشار 2005