From Distance Correlation to Multiscale Graph Correlation

26 Oct 2017Cencheng ShenCarey E. PriebeJoshua T. Vogelstein

Understanding and developing a correlation measure that can detect general dependencies is not only imperative to statistics and machine learning, but also crucial to general scientific discovery in the big data age. In this paper, we establish a new framework that generalizes distance correlation --- a correlation measure that was recently proposed and shown to be universally consistent for dependence testing against all joint distributions of finite moments --- to the Multiscale Graph Correlation (MGC)... (read more)

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