Robust nonparametric tests for the two-sample location problem
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Date
2011-05-27
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Abstract
We construct and investigate robust nonparametric tests for the two-sample
location problem. A test based on a suitable scaling of the median of the set
of differences between the two samples, which is the Hodges-Lehmann shift estimator
corresponding to the Wilcoxon two-sample rank test, leads to higher robustness
against outliers than the Wilcoxon test itself, while preserving its efficiency under a broad range of distributions. The good performance of the constructed test is investigated
under different distributions and outlier configurations and compared to
alternatives like the two-sample t-, the Wilcoxon and the median test, as well as
to tests based on the difference of the sample medians or the one-sample Hodges-
Lehmann estimators.
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Keywords
Distribution-free tests, Heavy tails, Outlier, Skewed distributions, Wilcoxon test