A nonparametric test of independence between 2 variables
Document Type
Article
Publication Date
12-1-2017
Abstract
A nonparametric statistic, called the roughness of concomitant ranks, is proposed for testing whether 2 quantitative vectors are dependent. The new testing procedure is highly computationally efficient and simple, and exhibits competitive empirical performance in simulations and 2 microarray data analyses. We apply the new method to screen variables for high-dimensional data analysis. For a low signal-to-noise ratio setting, we suggest the use of data binning to increase the power of the test. Simulation results show the fine performance of the proposed method with the existing screening methods.
Publication Source (Journal or Book title)
Statistical Analysis and Data Mining
First Page
422
Last Page
435
Recommended Citation
Li, B., & Yu, Q. (2017). A nonparametric test of independence between 2 variables. Statistical Analysis and Data Mining, 10 (6), 422-435. https://doi.org/10.1002/sam.11363