48 citations · 67 across the 7 of their papers we have counts for
13 papers
Robust High-Dimensional Regression with Coefficient Thresholding and its Application to Imaging Data Analysis
Bingyuan Liu, Qi Zhang, Lingzhou Xue +2
It is of importance to develop statistical techniques to analyze high-dimensional data in the presence of both complex dependence and possible outliers in real-world applications s…
Bayesian Hierarchical Models for High-Dimensional Mediation Analysis with Coordinated Selection of Correlated Mediators
Yanyi Song, Xiang Zhou, Jian Kang +9
We consider Bayesian high-dimensional mediation analysis to identify among a large set of correlated potential mediators the active ones that mediate the effect from an exposure va…
Statistical Inference for High-Dimensional Vector Autoregression with Measurement Error
Xiang Lyu, Jian Kang, Lexin Li
High-dimensional vector autoregression with measurement error is frequently encountered in a large variety of scientific and business applications. In this article, we study statis…
Bayesian Sparse Mediation Analysis with Targeted Penalization of Natural Indirect Effects
Yanyi Song, Xiang Zhou, Jian Kang +9
Causal mediation analysis aims to characterize an exposure's effect on an outcome and quantify the indirect effect that acts through a given mediator or a group of mediators of int…
Minorization-Maximization-based Steepest Ascent for Large-scale Survival Analysis with Time-Varying Effects: Application to the National Kidney Transplant Dataset
Kevin He, Ji Zhu, Jian Kang +1
The time-varying effects model is a flexible and powerful tool for modeling the dynamic changes of covariate effects. However, in survival analysis, its computational burden increa…
Bayesian Symbolic Regression
Ying Jin, Weilin Fu, Jian Kang +2
Interpretability is crucial for machine learning in many scenarios such as quantitative finance, banking, healthcare, etc. Symbolic regression (SR) is a classic interpretable machi…