The Rate of Convergence of Simple Linear Rank Statistics Under Hypothesis and Alternatives

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Abstract
Convergence rates for distributions of simple linear rank statistics are investigated. Both the null hypothesis and near alternatives are considered. The method of proof consists in approximating the characteristic function of the statistic by that of a sum of independent random variables and then applying standard tools.

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