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Abstract:
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In modern high-throughput applications, it is important to identify pairwise associations between variables and desirable to use methods that are powerful and sensitive to a variety of association relationships. We describe RankCover, a new non- parametric association test of association between two variables that measures the concentration of paired ranked points. Here,"concentration" is quantified using a disk- covering statistic similar to those employed in spatial data analysis. Considerations from the theory of Boolean coverage processes provide motivation, as well as an R 2-like quantity to summarize strength of association. Analysis of simulated and real datasets demonstrates that the method is robust and often powerful in comparison with competing general association tests
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