6 citations · 8 across the 8 of their papers we have counts for
8 papers
Robust Regression with Student's T: The Role of Degrees of Freedom
Amanda Ng, Shangkai Zhu, Archer Gong Zhang +1
Linear regression estimators are known to be sensitive to outliers, and one alternative to obtain a robust and efficient estimator of the regression parameter is to model the error…
Density ratio model for multiple types of survival data with empirical likelihood
James Hugh McVittie, Archer Gong Zhang
The density ratio model (DRM) is a semiparametric model that relates the distributions from multiple samples to a nonparametrically defined reference distribution via exponential t…
A Semiparametric Approach to Causal Inference
Archer Gong Zhang, Nancy Reid, Qiang Sun
In causal inference, an important problem is to quantify the effects of interventions or treatments. Many studies focus on estimating the mean causal effects; however, these estima…
Optimal Estimation under a Semiparametric Density Ratio Model
Archer Gong Zhang, Jiahua Chen
In many statistical and econometric applications, we gather individual samples from various interconnected populations that undeniably exhibit common latent structures. Utilizing a…
Density ratio model with data-adaptive basis function
Archer Gong Zhang, Jiahua Chen
In many applications, we collect independent samples from interconnected populations. These population distributions share some latent structure, so it is advantageous to jointly a…
Empirical likelihood ratio test on quantiles under a density ratio model
Archer Gong Zhang, Guangyu Zhu, Jiahua Chen
Population quantiles are important parameters in many applications. Enthusiasm for the development of effective statistical inference procedures for quantiles and their functions h…
Gaussian Mixture Reduction with Composite Transportation Divergence
Qiong Zhang, Archer Gong Zhang, Jiahua Chen
Gaussian mixtures are widely used for approximating density functions in various applications such as density estimation, belief propagation, and Bayesian filtering. These applicat…
Resistant convex clustering: How does the fusion penalty enhance resistantance?
Qiang Sun, Archer Gong Zhang, Chenyu Liu +1
Convex clustering is a convex relaxation of the -means and hierarchical clustering. It involves solving a convex optimization problem with the objective function being a squared…