A New Class of Measures for Independence Test with Its Application in Big Data

• Activity Number: 604
• Type: Contributed
• Date/Time: Wednesday, August 3, 2016 : 2:00 PM to 3:50 PM
• Sponsor: Section on Statistical Computing
• Author(s): Qingcong Yuan* and Xiangrong Yin
• Companies: University of Kentucky and University of Kentucky
• Keywords: Categorical variable ; Distance ; Independence ; Sufficient variable selection

Abstract

We introduce a new class of measures for testing independence between two random vectors, using characteristic functions. In this talk, by choosing a particular weight function in the class, we study a new index for measuring independence and its property. Sample versions and their asymptotic properties using different estimations are developed. We demonstrate the advantage of our methods via simulations and real data. In particular, we illustrate the effective use of our methods in big data analysis.