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Nonparametric Confidence Regions for Some Multivariate Location Problems

机译:一些多元定位问题的非参数置信区域

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摘要

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. Specifically, nonparametric confidence regions based on Bonferroni inequality, the maximum modulus, and Scheffe's method are studied. The results obtained are nonparametric generalizations of some of the results of Dunn and Sidak. Certain optimality properties of the proposed methods are also established. (Author)

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