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Pseudo-likelihood ratio tests for semiparametric multivariate copula model selection. (English) Zbl 1077.62032
Summary: 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 nonnested or generalized nested. For more than two models, the procedure is built on the reality check test of H. White [Econometrica 68, No. 5, 1097–1126 (2000; Zbl 1008.62116)]. Unlike White, however, the test statistic is automatically standardized for generalized nonnested models (with a benchmark) and ignores generalized nested models asymptotically. The authors illustrate their approach with American insurance claim data.

MSC:
62G10 Nonparametric hypothesis testing
62H15 Hypothesis testing in multivariate analysis
62G20 Asymptotic properties of nonparametric inference
62P05 Applications of statistics to actuarial sciences and financial mathematics
62L10 Sequential statistical analysis
62G09 Nonparametric statistical resampling methods
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