A SEMIPARAMETRIC ESTIMATION PROCEDURE OF DEPENDENCE PARAMETERS IN MULTIVARIATE FAMILIES OF DISTRIBUTIONS

This paper investigates the properties of a semiparametric method for estimating the dependence parameters in a family of multivariate distr ibutions. The proposed estimator, obtained as a solution of a pseudo-l ikelihood equation, is shown to be consistent, asymptotically normal a nd fully efficient at independence. A natural estimator of its asympto tic variance is proved to be consistent. Comparisons are made with alt ernative semiparametric estimators in the special case of Clayton's mo del for association in bivariate data.