Lingzhou Xue
Associate Professor of Statistics
-
318 Thomas
University Park, PA - lxx6@psu.edu
- 814-865-1290
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 GasMost 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