par Paindaveine, Davy
Référence Statistical Methodology, 1, page (81-91)
Publication Publié, 2004
Article révisé par les pairs
Résumé : We provide a simple proof that the Chernoff-Savage [H. Chernoff, I.R. Savage, Asymptotic normality and efficiency of certain nonparametric tests, Ann. Math. Statist. 29 (1958) 972-994] result, establishing the uniform dominance of normal-score rank procedures over their Gaussian competitors, also holds in a broad class of problems involving serial and/or multivariate observations. The non-admissibility of the corresponding everyday practice Gaussian procedures (multivariate least-squares estimators, multivariate t-tests and F-tests, correlogram-based methods, multivariate portmanteau and Durbin-Watson tests, etc.) follows. The proof, which generalizes to the multivariate - possibly serial - set-up the idea developed in J.L. Gastwirth, S.S. Wolff [An elementary method for obtaining lower bounds on the asymptotic power of rank tests, Ann. Math. Statist. 39 (1968) 2128-2130] in the context of univariate location problems, allows for avoiding technical convexity and variational arguments.