  In this paper, a class of statistics named ART (the alternant recursive
topology statistics) is proposed to measure the properties of correlation
between two variables. A wide range of bi-variable correlations both linear and
nonlinear can be evaluated by ART efficiently and equitably even if nothing is
known about the specific types of those relationships. ART compensates the
disadvantages of Reshef's model in which no polynomial time precise algorithm
exists and the "local random" phenomenon can not be identified. As a class of
nonparametric exploration statistics, ART is applied for analyzing a dataset of
10 American classical indexes, as a result, lots of bi-variable correlations
are discovered.
