Runze Li
Co-Director of the Center for Statistical Genetics; Eberly Family Chair and Associate Department Head in Statistics
-
326 Thomas
University Park, PA 16802 - ril4@psu.edu
- 814-895-1555
Huck Affiliations
Most Recent Publications
Projection test with sparse optimal direction for high-dimensional one-sample mean problem
Wanjun Liu, Runze Li, on p. 295-309
Compositional variable selection in quantile regression for microbiome data with false discovery rate control
Runze Li, Jin Mu, Songshan Yang, Cong Ye, Xiang Zhan, 2024, Statistical Analysis and Data Mining
PROPENSITY SCORE REGRESSION FOR CAUSAL INFERENCE WITH TREATMENT HETEROGENEITY
Peng Wu, Shasha Han, Xingwei Tong, Runze Li, 2024, Statistica Sinica on p. 747-769
RANK-BASED INDICES FOR TESTING INDEPENDENCE BETWEEN TWO HIGH-DIMENSIONAL VECTORS
Yeqing Zhou, Kai Xu, Liping Zhu, Runze Li, 2024, Annals of Statistics on p. 184-206
Reprint: Statistical inference for linear mediation models with high-dimensional mediators and application to studying stock reaction to COVID-19 pandemic
Xu Guo, Runze Li, Jingyuan Liu, Mudong Zeng, 2024, Journal of Econometrics
Data science in economics and finance: Introduction
Matias D. Cattaneo, Yingying Fan, Runze Li, Rui Song, 2024, Journal of Econometrics
Tests for Large-Dimensional Shape Matrices via Tyler’s M Estimators
Runze Li, Weiming Li, Qinwen Wang, 2024, Journal of the American Statistical Association
TransFusion: Covariate-Shift Robust Transfer Learning for High-Dimensional Regression
Zelin He, Ying Sun, Jingyuan Liu, Runze Li, 2024, Proceedings of Machine Learning Research on p. 703-711
Generalized Varying Coefficient Mediation Models
Jingyuan Liu, Yujie Liao, Runze Li, 2024, Communications in Mathematics and Statistics
Invariance Principle and CLT for the Spiked Eigenvalues of Large-dimensional Fisher Matrices and Applications
Dandan Jiang, Z Hou, Zhidong Bai, Runze Li, 2024, Statistica Sinica
Most-Cited Papers
Sensitivity and specificity of information criteria
John J. Dziak, Donna L. Coffman, Stephanie T. Lanza, Runze Li, Lars S. Jermiin, 2020, Briefings in Bioinformatics on p. 553-565
Model-Free Feature Screening for Ultrahigh Dimensional Discriminant Analysis
Hengjian Cui, Runze Li, Wei Zhong, 2015, Journal of the American Statistical Association on p. 630-641
A High-Dimensional Nonparametric Multivariate Test for Mean Vector
Lan Wang, Bo Peng, Runze Li, 2015, Journal of the American Statistical Association on p. 1658-1669
Projection correlation between two random vectors
Liping Zhu, Kai Xu, Runze Li, Wei Zhong, 2017, Biometrika on p. 829-843
A selective overview of feature screening for ultrahigh-dimensional data
Jing Yuan Liu, Wei Zhong, Run Ze Li, 2015, Science China Mathematics
Variable Screening via Quantile Partial Correlation
Shujie Ma, Runze Li, Chih Ling Tsai, 2017, Journal of the American Statistical Association on p. 650-663
Variable selection for support vector machines in moderately high dimensions
Xiang Zhang, Yichao Wu, Lan Wang, Runze Li, 2016, Journal of the Royal Statistical Society. Series B: Statistical Methodology on p. 53-76
Bayesian group lasso for nonparametric varying-coefficient models with application to functional genome-wide association studies
Jiahan Li, Zhong Wang, Runze Li, Rongling Wu, 2015, Annals of Applied Statistics on p. 640-664
Ultrahigh-Dimensional Multiclass Linear Discriminant Analysis by Pairwise Sure Independence Screening
Rui Pan, Hansheng Wang, Runze Li, 2016, Journal of the American Statistical Association on p. 169-179
Depression and marijuana use disorder symptoms among current marijuana users
Lisa Dierker, Arielle Selya, Stephanie Lanza, Runze Li, Jennifer Rose, 2018, Addictive Behaviors on p. 161-168
News Articles Featuring Runze Li
Jul 18, 2023
Two honored with Eberly Distinguished Faculty Mentoring Award
Two members of the Eberly College of Science have been selected to receive the college's Distinguished Faculty Mentoring Award in 2023.
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Nov 20, 2019
Eleven Eberly faculty featured as highly cited researchers in 2019 by Clarivate
Eleven researchers from the Eberly College of Science have been recognized as "highly cited" by the Clarivate Analytics Web of Science Group. The 2019 Highly Cited Researchers list features researchers who have demonstrated considerable influence through publication of multiple works that have been cited by a significant number of their peers during the last decade.
Full Article