Testing Independence with the Binary Expansion Randomized Ensemble Test

12/08/2019
by   Duyeol Lee, et al.
0

Recently, the binary expansion testing framework was introduced to test the independence of two continuous random variables by utilizing symmetry statistics that are complete sufficient statistics for dependence. We develop a new test by an ensemble method that uses the sum of squared symmetry statistics and distance correlation. Simulation studies suggest that this method improves the power while preserving the clear interpretation of the binary expansion testing. We extend this method to tests of independence of random vectors in arbitrary dimension. By random projections, the proposed binary expansion randomized ensemble test transforms the multivariate independence testing problem into a univariate problem. Simulation studies and data example analyses show that the proposed method provides relatively robust performance compared with existing methods.

READ FULL TEXT
research
10/17/2016

BET on Independence

We study the problem of nonparametric dependence detection. Many existin...
research
04/26/2022

Discussion of Multiscale Fisher's Independence Test for Multivariate Dependence

The multiscale Fisher's independence test (MULTIFIT hereafter) proposed ...
research
03/01/2021

BEAUTY Powered BEAST

We study inference about the uniform distribution with the proposed bina...
research
09/28/2021

The AUGUST Two-Sample Test: Powerful, Interpretable, and Fast

Two-sample testing is a fundamental problem in statistics, and many famo...
research
06/05/2019

A novel characterization and new simple tests of multivariate independence using copulas

The purpose of this paper is twofold. First, we provide a novel characte...
research
01/09/2014

Efficient unimodality test in clustering by signature testing

This paper provides a new unimodality test with application in hierarchi...
research
05/05/2021

A nonparametric test of independence based on L_1-error

We propose a test of mutual independence between random vectors with arb...

Please sign up or login with your details

Forgot password? Click here to reset