Data-driven rank tests for independence

Nonparametric statistics independence is tested using data-driven rank tests. The proposed tests are sensitive for both grade linear correlation and grade correlations of higher-order polynomials. Monte Carlo simulation results show that the rank tests possess greater power stability than other well-known tests such as Spearman's test or Hoeffding's test. The consistency of the tests is proven to obtain theoretical support.
1. INTRODUCTION In many statistical studies we are interested in the relationship between several quantities - in particular, the independence of random measurements. Under bivariate normality, dependence is completely described [...]