| Multivariate sign-based high-dimensional tests for sphericity C Zou, L Peng, L Feng, Z Wang Biometrika 101 (1), 229-236, 2014 | 57 | 2014 |
| Distributed statistical inference for massive data SX Chen, L Peng The Annals of Statistics 49 (5), 2851-2869, 2021 | 24 | 2021 |
| More powerful tests for sparse high-dimensional covariances matrices L Peng, SX Chen, W Zhou Journal of Multivariate Analysis 149, 124-143, 2016 | 12 | 2016 |
| Nonparametric feature selection by random forests and deep neural networks X Mao, L Peng, Z Wang Computational Statistics & Data Analysis 170, 107436, 2022 | 9 | 2022 |
| Testing the equality of two high‐dimensional spatial sign covariance matrices G Cheng, B Liu, L Peng, B Zhang, S Zheng Scandinavian Journal of Statistics 46 (1), 257-271, 2019 | 9 | 2019 |
| Simultaneous confidence bands for conditional value-at-risk and expected shortfall S Li, L Peng, X Song Econometric Theory 39 (5), 1009-1043, 2023 | 5 | 2023 |
| Bootstrap inference for the finite population mean under complex sampling designs Z Wang, L Peng, JK Kim Journal of the Royal Statistical Society Series B: Statistical Methodology …, 2022 | 5* | 2022 |
| Distributed inference for two‐sample U‐statistics in massive data analysis B Huang, Y Liu, L Peng Scandinavian Journal of Statistics 50 (3), 1090-1115, 2023 | 4 | 2023 |
| Uncertainty quantification in depth estimation via constrained ordinal regression D Hu, L Peng, T Chu, X Zhang, Y Mao, H Bondell, M Gong European Conference on Computer Vision, 237-256, 2022 | 3 | 2022 |
| Testing independence between exogenous variables and unobserved errors S Li, L Peng, Y Tu Econometric Reviews 41 (7), 697-728, 2022 | 3* | 2022 |
| Weighted bootstrap for two-sample u-statistics B Huang, Y Liu, L Peng Journal of Statistical Planning and Inference 226, 86-99, 2023 | 1 | 2023 |
| Statistical inference for ultrahigh dimensional location parameter based on spatial median G Cheng, L Peng, C Zou arXiv preprint arXiv:2301.03126, 2023 | 1 | 2023 |
| Extreme Continuous Treatment Effects: Measures, Estimation and Inference W Huang, S Li, L Peng arXiv preprint arXiv:2209.00246, 2022 | 1 | 2022 |
| Beta mixture model for the uncertainties in robotic haptic object identification Y Xia, A Mohammadi, L Peng, Y Tan, B Chen, P Choong, D Oetomo IEEE/ASME Transactions on Mechatronics 27 (4), 1955-1963, 2022 | 1 | 2022 |
| Gaussian approximations for high-dimensional non-degenerate U-statistics via exchangeable pairs G Cheng, Z Liu, L Peng Statistics & Probability Letters 182, 109295, 2022 | 1 | 2022 |
| Supplement to “Distributed statistical inference for massive data.” SX Chen, L Peng | 1 | 2021 |
| Postural behaviour in people with multiple sclerosis: a complexity paradox LEC Lizama, MG Panisset, L Peng, Y Tan, T Kalincik, MP Galea Gait & Posture, 2024 | | 2024 |
| MEASURING, TESTING, AND IDENTIFYING HETEROGENEITY OF LARGE PARALLEL DATASETS L Peng, G Wang, C Zou Statistica Sinica 33 (4), 2787-2808, 2023 | | 2023 |
| Optimal sensor location and direction to accurately classify people with early-stage multiple sclerosis using gait stability LEC Lizama, MG Panisset, L Peng, Y Tan, T Kalincik, MP Galea Gait & Posture 102, 39-42, 2023 | | 2023 |
| Non-linear Measures of Gait Adaptability in Multiple Sclerosis-Sensitivity and Neurological Correlates MG Panisset, LEC Lizama, L Peng, MP Galea medRxiv, 2022.07. 06.22277289, 2022 | | 2022 |
