arxivst stuff from arxiv that you should probably bookmark

Copula Index for Detecting Dependence and Monotonicity between Stochastic Signals

Abstract · Mar 20, 2017 11:26 ·

stat-ml q-bio-qm

Arxiv Abstract

  • Kiran Karra
  • Lamine Mili

This paper introduces a nonparametric copula-based approach for detecting the strength and monotonicity of linear and nonlinear statistical dependence between bivariate continuous, discrete or hybrid random variables and stochastic signals, termed CIM. We show that CIM satisfies the data processing inequality and is consequently a self-equitable metric. Simulation results using synthetic datasets reveal that the CIM compares favorably to other state-of-the-art statistical dependency metrics, including the Maximal Information Coefficient (MIC), Randomized Dependency Coefficient (RDC), distance Correlation (dCor), Copula correlation (Ccor), and Copula Statistic (CoS) in both statistical power and sample size requirements. Simulations using real world data highlight the importance of understanding the monotonicity of the dependence structure.

Read the paper (pdf) »