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Keywords:
dependence function; multivariate rank statistics; semiparametric inference; copulas; boundary; divergences; duality
dependence function; multivariate rank statistics; semiparametric inference; copulas; boundary; divergences; duality
Summary:
We introduce new estimates and tests of independence in copula models with unknown margins using $\phi$-divergences and the duality technique. The asymptotic laws of the estimates and the test statistics are established both when the parameter is an interior or a boundary value of the parameter space. Simulation results show that the choice of $\chi^2$-divergence has good properties in terms of efficiency-robustness.
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