5 citations · 11 across the 4 of their papers we have counts for
4 papers
Testing for Conditional Mean Independence with Covariates through Martingale Difference Divergence
Ze Jin, Xiaohan Yan, David S. Matteson
As a crucial problem in statistics is to decide whether additional variables are needed in a regression model. We propose a new multivariate test to investigate the conditional mea…
Independent Component Analysis via Energy-based and Kernel-based Mutual Dependence Measures
Ze Jin, David S. Matteson
We apply both distance-based (Jin and Matteson, 2017) and kernel-based (Pfister et al., 2016) mutual dependence measures to independent component analysis (ICA), and generalize dCo…
Optimization and Testing in Linear Non-Gaussian Component Analysis
Ze Jin, Benjamin B. Risk, David S. Matteson
Independent component analysis (ICA) decomposes multivariate data into mutually independent components (ICs). The ICA model is subject to a constraint that at most one of these com…
Generalizing Distance Covariance to Measure and Test Multivariate Mutual Dependence
Ze Jin, David S. Matteson
We propose three measures of mutual dependence between multiple random vectors. All the measures are zero if and only if the random vectors are mutually independent. The first meas…