| Quantile regression for analyzing heterogeneity in ultra-high dimension L Wang, Y Wu, R Li Journal of the American Statistical Association 107 (497), 214-222, 2012 | 370 | 2012 |
| Quantile-adaptive model-free variable screening for high-dimensional heterogeneous data X He, L Wang, HG Hong | 307 | 2013 |
| Locally weighted censored quantile regression HJ Wang, L Wang Journal of the American Statistical Association 104 (487), 1117-1128, 2009 | 279 | 2009 |
| Penalized generalized estimating equations for high-dimensional longitudinal data analysis L Wang, J Zhou, A Qu Biometrics 68 (2), 353-360, 2012 | 216 | 2012 |
| Calibrating non-convex penalized regression in ultra-high dimension L Wang, Y Kim, R Li Annals of statistics 41 (5), 2505, 2013 | 207 | 2013 |
| A high-dimensional nonparametric multivariate test for mean vector L Wang, B Peng, R Li Journal of the American Statistical Association 110 (512), 1658-1669, 2015 | 165 | 2015 |
| Partially linear additive quantile regression in ultra-high dimension B Sherwood, L Wang | 156 | 2016 |
| GEE analysis of clustered binary data with diverging number of covariates L Wang | 129 | 2011 |
| An iterative coordinate descent algorithm for high-dimensional nonconvex penalized quantile regression B Peng, L Wang Journal of Computational and Graphical Statistics 24 (3), 676-694, 2015 | 111 | 2015 |
| Quantile-optimal treatment regimes L Wang, Y Zhou, R Song, B Sherwood Journal of the American Statistical Association 113 (523), 1243-1254, 2018 | 92 | 2018 |
| Consistent model selection and data-driven smooth tests for longitudinal data in the estimating equations approach L Wang, A Qu Journal of the Royal Statistical Society Series B: Statistical Methodology …, 2009 | 89 | 2009 |
| Variable selection for support vector machines in moderately high dimensions X Zhang, Y Wu, L Wang, R Li Journal of the Royal Statistical Society Series B: Statistical Methodology …, 2016 | 88 | 2016 |
| Weighted Wilcoxon-type smoothly clipped absolute deviation method L Wang, R Li Biometrics 65 (2), 564-571, 2009 | 84 | 2009 |
| Local rank inference for varying coefficient models L Wang, B Kai, R Li Journal of the American Statistical Association 104 (488), 1631-1645, 2009 | 77 | 2009 |
| Weighted quantile regression for analyzing health care cost data with missing covariates B Sherwood, L Wang, XH Zhou Statistics in medicine 32 (28), 4967-4979, 2013 | 75 | 2013 |
| A tuning-free robust and efficient approach to high-dimensional regression L Wang, B Peng, J Bradic, R Li, Y Wu Journal of the American Statistical Association 115 (532), 1700-1714, 2020 | 65 | 2020 |
| Comparing large covariance matrices under weak conditions on the dependence structure and its application to gene clustering J Chang, W Zhou, WX Zhou, L Wang Biometrics 73 (1), 31-41, 2017 | 62 | 2017 |
| High-dimensional quantile regression: Convolution smoothing and concave regularization KM Tan, L Wang, WX Zhou Journal of the Royal Statistical Society Series B: Statistical Methodology …, 2022 | 59 | 2022 |
| A parallel algorithm for large-scale nonconvex penalized quantile regression L Yu, N Lin, L Wang Journal of Computational and Graphical Statistics 26 (4), 935-939, 2017 | 58 | 2017 |
| An ANOVA-type nonparametric diagnostic test for heteroscedastic regression models L Wang, MG Akritas, I Van Keilegom Journal of Nonparametric Statistics 20 (5), 365-382, 2008 | 48 | 2008 |
