37 citations · 38 across the 5 of their papers we have counts for
5 papers
Varying Coefficient Model via Adaptive Spline Fitting
Xufei Wang, Bo Jiang, Jun S. Liu
The varying coefficient model has received broad attention from researchers as it is a powerful dimension reduction tool for non-parametric modeling. Most existing varying coeffici…
Kernel-based Partial Permutation Test for Detecting Heterogeneous Functional Relationship
Xinran Li, Bo Jiang, Jun S. Liu
We propose a kernel-based partial permutation test for checking the equality of functional relationship between response and covariates among different groups. The main idea, which…
Generalized R-squared for Detecting Dependence
Xufei Wang, Bo Jiang, Jun S. Liu
Detecting dependence between two random variables is a fundamental problem. Although the Pearson correlation is effective for capturing linear dependency, it can be entirely powerl…
Bayesian nonparametric tests via sliced inverse modeling
Bo Jiang, Chao Ye, Jun S. Liu
We study the problem of independence and conditional independence tests between categorical covariates and a continuous response variable, which has an immediate application in gen…
Variable selection for general index models via sliced inverse regression
Bo Jiang, Jun S. Liu
Variable selection, also known as feature selection in machine learning, plays an important role in modeling high dimensional data and is key to data-driven scientific discoveries.…