A semiparametric estimation procedure of dependence parameters in multivariate families of distributions

This paper investigates the properties of a semiparametric methodfor estimating the dependence parameters in a family of multivariatedistributions. The proposed estimator, obtained as a solutionof a pseudo-likelihood equation, is shown to be consistent,asymptotically normal and fully efficient at independence. Anatural estimator of its asymptotic variance is proved to beconsistent. Comparisons are made with alternative semiparametricestimators in the special case of Clayton's model for associationin bivariate data.