This paper investigates the effects of dependence on rank tests, in particular on a class of recently defined nonparametric tests called '%'mixed'%' statistical tests. It is shown that the mixed test statistic is asymptotically normal for gaussian processes with mild regularity properties justifying the use of asymptotic relative efficiency (ARE) as a figure of merit. Results are presented in terms of variations on three well-known statistics- the one- sample Wilcoxon, the two-sample Mann- Whitney, and the Kendall tau. It is found that the effects ofof dependence on ARE with respect to a parametric test can be offset to some extent by appropriately grouping sample values. If, however, a constant false-alarm rate is to be attained, either the form of the dependence must be known or some learning scheme must be applied.
ASJC Scopus subject areas
- Information Systems
- Computer Science Applications
- Library and Information Sciences