Runze Li

Co-Director of the Center for Statistical Genetics; Eberly Family Chair and Associate Department Head in Statistics

Runze Li

Huck Affiliations

Publication Tags

Screening Covariates Estimator High Dimensional Simulation Study Performance Model Statistical Inference Sample Size Confidence Interval Predictors Statistics Variable Selection Monte Carlo Simulation Inference Conditional Distribution Discriminant Analysis Correlation Matrix Learning Partially Linear Model Time Tobacco Products Quantile Regression Feature Selection Higher Dimensions

Most Recent Papers

Stable correlation and robust feature screening

Xu Guo, Runze Li, Wanjun Liu, Lixing Zhu, 2022, Science China Mathematics on p. 153-168

Trajectories of mortality risk among patients with cancer and associated end-of-life utilization

Ravi B. Parikh, Manqing Liu, Eric Li, Runze Li, Jinbo Chen, 2021, npj Digital Medicine

Inference in high dimensional linear measurement error models

Mengyan Li, Runze Li, Yanyuan Ma, 2021, Journal of Multivariate Analysis

Feature screening for network autoregression model

Danyang Huang, Xuening Zhu, Runze Li, Hansheng Wang, 2021, Statistica Sinica on p. 1239-1259

Central limit theorem for linear spectral statistics of large dimensional Kendall's rank correlation matrices and its applications

Zeng Li, Qinwen Wang, Runze Li, 2021, Annals of Statistics on p. 1569-1593

Folded concave penalized learning of high-dimensional MRI data in Parkinson's disease

Changcheng Li, Xue Wang, Guangwei Du, Hairong Chen, Gregory Brown, Mechelle M. Lewis, Tao Yao, Runze Li, Xuemei Huang, 2021, Journal of Neuroscience Methods

Variable selection for partially linear models via Bayesian subset modeling with diffusing prior

Jia Wang, Xizhen Cai, Runze Li, 2021, Journal of Multivariate Analysis

The association between short-term emotion dynamics and cigarette dependence

Anne Buu, Zhanrui Cai, Runze Li, Su Wei Wong, Hsien Chang Lin, Wei Chung Su, Douglas E. Jorenby, Megan E. Piper, 2021, Drug and Alcohol Dependence

Inference on covariance-mean regression

Tao Zou, Wei Lan, Runze Li, Chih Ling Tsai, 2021, Journal of Econometrics

Statistical Inference for High-Dimensional Models via Recursive Online-Score Estimation

Chengchun Shi, Rui Song, Wenbin Lu, Runze Li, 2021, Journal of the American Statistical Association on p. 1307-1318

Most-Cited Papers

Feature screening via distance correlation learning

Runze Li, Wei Zhong, Liping Zhu, 2012, Journal of the American Statistical Association on p. 1129-1139

A time-varying effect model for intensive longitudinal data

Xianming Tan, Mariya P. Shiyko, Runze Li, Yuelin Li, Lisa Dierker, 2012, Psychological Methods on p. 61-77

Quantile regression for analyzing heterogeneity in ultra-high dimension

Lan Wang, Yichao Wu, Runze Li, 2012, Journal of the American Statistical Association on p. 214-222

Feature selection for varying coefficient models with ultrahigh-dimensional covariates

Jingyuan Liu, Runze Li, Rongling Wu, 2014, Journal of the American Statistical Association on p. 266-274

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

Using the Time-Varying Effect Model (TVEM) to Examine Dynamic Associations between Negative Affect and Self Confidence on Smoking Urges

Mariya P. Shiyko, Stephanie T. Lanza, Xianming Tan, Runze Li, Saul Shiffman, 2012, Prevention Science on p. 288-299

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

Calibrating nonconvex penalized regression in ultra-high dimension

Lan Wang, Yongdai Kim, Runze Li, 2013, Annals of Statistics on p. 2505-2536

Local modal regression

Weixin Yao, Bruce G. Lindsay, Runze Li, 2012, Journal of Nonparametric Statistics on p. 647-663

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