Abstract
Abstract Nonparametric methods of constructing confidence regions for the location vectors in the multivariate one-sample and two-sample problems are provided. These methods are based on a class of rank order statistics studied in detail by the authors in [8, 9, 11, 13]. Specifically, nonparametric confidence regions based on the Bonferroni inequality, the maximum modulus, and Scheffé's method are studied. The results obtained are nonparametric generalizations of some of the results of Dunn [3, 4] and SIdák [15]. Certain optimality properties of the proposed methods are also established.
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