One- and two-sample nonparametric tests for the signal-to-noise ratio based on record statistics
Abstract
A new family of nonparametric statistics, the r-statistics, is introduced. It consists of counting the number of records of the cumulative sum of the sample. The single-sample r-statistic is almost as powerful as Student's t-statistic for Gaussian and uniformly distributed variables, and more powerful than the sign and Wilcoxon signed-rank statistics as long as the data are not too heavy-tailed. Three two-sample parametric r-statistics are proposed, one with a higher specificity but a smaller sensitivity than Mann-Whitney U-test and the other one a higher sensitivity but a smaller specificity. A nonparametric two-sample r-statistic is introduced, whose power is very close to that of Welch statistic for Gaussian or uniformly distributed variables.
Cite
@article{arxiv.1502.05367,
title = {One- and two-sample nonparametric tests for the signal-to-noise ratio based on record statistics},
author = {Damien Challet},
journal= {arXiv preprint arXiv:1502.05367},
year = {2015}
}
Comments
12 pages, 13 figures