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A simple algorithm for the adaptation of scores and power behavior of the corresponding rank test
Authors:Konrad Behnen  Marie Huškové
Institution:1. University of Hamburg , West Germany;2. University of Prague , Czechoslovakia
Abstract:The purpose of this paper is twofold:On one hand we want to give a very simple algorithm for evaluating a special rank estimator of the type given in Behnen, Neuhaus, and Ruymgaart (1983) for the approximate optimal choice of the scores-generating function of a two-sample linear rank test for the general testing problem Ho:F=G versus H1:F ≤ G, F ≠ G, in order to demonstrate that the corresponding adaptive rank statistic is simple enough for practical applications. On the other hand we prove the asymptotic normality of the adaptive rank statistic under H (leading to approximate critical values) and demonstrate the adaptive behavior of the corresponding rank test by a Monte Carlo power simulation for sample sizes as low as m=10, n=10.
Keywords:adaptive rank tests  two-sample problem  stochastically-larger-alternatives  rank estimators of score-functions  asymptotic normality  power simulation
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