Lingzhou Xue

Associate Professor of Statistics

Lingzhou Xue

Research Summary

High-dimensional statistics, statistical learning, optimization, econometrics, and statistical applications in biological science, environmental science, and social science.

Huck Affiliations

Links

Publication Tags

Regression Analysis Estimator Principal Component Analysis Platelets High Dimensional Performance Screening Graphical Models Covariance Matrix Network Model Optimality Simulation Ligands Model Sufficient Neural Networks Violence Forecasting Contamination Agglomeration Leucine Latent Variables Nonparametric Estimation Water Pollution Shale Gas

Most Recent Papers

Applications of Peter Hall’s Martingale Limit Theory to Estimating and Testing High Dimensional Covariance Matrices

Lingzhou Xue, Danning Li, Hui Zou, Statistica Sinica

Improving neural network robustness through neighborhood preserving layers

Bingyuan Liu, Christopher Malon, Lingzhou Xue, Erik Kruus, 2022, Image and Vision Computing

Estimating Finite Mixtures of Ordinal Graphical Models

Kevin H. Lee, Qian Chen, Wayne S. DeSarbo, Lingzhou Xue, 2022, Psychometrika on p. 83-106

Nonparametric Estimation and Conformal Inference of the Sufficient Forecasting With a Diverging Number of Factors

Xiufan Yu, Jiawei Yao, Lingzhou Xue, 2022, Journal of Business and Economic Statistics on p. 342-354

Compositional knockoff filter for high-dimensional regression analysis of microbiome data

Arun Srinivasan, Lingzhou Xue, Xiang Zhan, 2021, Biometrics on p. 984-995

Improving Neural Network Robustness Through Neighborhood Preserving Layers

Bingyuan Liu, Christopher Malon, Lingzhou Xue, Erik Kruus, 2021, on p. 179-195

Statisticians Engage in Gun Violence Research

Greg Ridgeway, James L. Rosenberger, Lingzhou Xue, 2021, Statistics and Public Policy on p. 73-79

Assessing Contamination of Stream Networks near Shale Gas Development Using a New Geospatial Tool

Amal Agarwal, Tao Wen, Alex Chen, Anna Yinqi Zhang, Xianzeng Niu, Xiang Zhan, Lingzhou Xue, Susan L. Brantley, 2020, Environmental Science & Technology on p. 8632-8639

Diagonally Dominant Principal Component Analysis

Zheng Tracy Ke, Lingzhou Xue, Fan Yang, 2020, Journal of Computational and Graphical Statistics on p. 592-607

Model-Based Clustering of Nonparametric Weighted Networks With Application to Water Pollution Analysis

Amal Agarwal, Lingzhou Xue, 2020, Technometrics on p. 161-172

Most-Cited Papers

Strong oracle optimality of folded concave penalized estimation

Jianqing Fan, Lingzhou Xue, Hui Zou, 2014, Annals of Statistics on p. 819-849

Regularized rank-based estimation of high-dimensional nonparanormal graphical models

Lingzhou Xue, Hui Zou, 2012, Annals of Statistics on p. 2541-2571

Positive-definite l<sub>1</sub>-penalized estimation of large covariance matrices

Lingzhou Xue, Shiqian Ma, Hui Zou, 2012, Journal of the American Statistical Association on p. 1480-1491

Alternating direction methods for latent variable gaussian graphical model selection

Shiqian Ma, Lingzhou Xue, Hui Zou, 2013, Neural Computation on p. 2172-2198

An integrin α<sub>IIb</sub>β<sub>3</sub> intermediate affinity state mediates biomechanical platelet aggregation

Yunfeng Chen, Lining Arnold Ju, Fangyuan Zhou, Jiexi Liao, Lingzhou Xue, Qian Peter Su, Dayong Jin, Yuping Yuan, Hang Lu, Shaun P. Jackson, Cheng Zhu, 2019, Nature Materials on p. 760-769

Cooperative unfolding of distinctive mechanoreceptor domains transduces force into signals

Lining Ju, Yunfeng Chen, Lingzhou Xue, Xiaoping Du, Cheng Zhu, 2016, eLife

A Selective Overview of Sparse Principal Component Analysis

Hui Zou, Lingzhou Xue, 2018, Proceedings of the Institute of Radio Engineers on p. 1311-1320

A review of dynamic network models with latent variables

Bomin Kim, Kevin H. Lee, Lingzhou Xue, Xiaoyue Niu, 2018, Statistics Surveys on p. 105-135

Nonconcave penalized composite conditional likelihood estimation of sparse ising models

Lingzhou Xue, Hui Zou, Tianxi Cai, 2012, Annals of Statistics on p. 1403-1429

Sufficient forecasting using factor models

Jianqing Fan, Lingzhou Xue, Jiawei Yao, 2017, Journal of Econometrics on p. 292-306