| Banded Spatio-Temporal Autoregressions Z Gao, Y Ma, H Wang, Q Yao Journal of Econometrics 208, 211-230, 2019 | 37 | 2019 |
| A high dimensional two-sample test under a low dimensional factor structure Y Ma, W Lan, H Wang Journal of Multivariate Analysis 140, 162-170, 2015 | 29 | 2015 |
| A naive least squares method for spatial autoregression with covariates Y Ma, R Pan, T Zou, H Wang Statistica Sinica 30 (2), 653-672, 2020 | 16 | 2020 |
| Sparse Spatio-Temporal Autoregressions by Profiling and Bagging Y Ma, S Guo, H Wang Journal of Econometrics 232 (1), 132-147, 2021 | 14 | 2021 |
| Sequential Model Averaging for High Dimensional Linear Regression Models W Lan, Y Ma, J Zhao, H Wang, CL Tsai Statistica Sinica 28, 449-469, 2018 | 7 | 2018 |
| A selective review on statistical methods for massive data computation: distributed computing, subsampling, and minibatch techniques X Li, Y Gao, H Chang, D Huang, Y Ma, R Pan, H Qi, F Wang, S Wu, K Xu, ... Statistical Theory and Related Fields, 1-23, 2024 | 6 | 2024 |
| Optimal subsampling bootstrap for massive data Y Ma, C Leng, H Wang Journal of Business & Economic Statistics 42 (1), 174-186, 2024 | 6 | 2024 |
| Approximate least squares estimation for spatial autoregressive models with covariates Y Ma, W Lan, F Zhou, H Wang Computational Statistics & Data Analysis 143, 106833, 2020 | 4 | 2020 |
| Semiparametric model for covariance regression analysis J Liu, Y Ma, H Wang Computational Statistics & Data Analysis 142, 106815, 2020 | 4 | 2020 |
| Testing predictor significance with ultra high dimensional multivariate responses Y Ma, W Lan, H Wang Computational Statistics & Data Analysis 83, 275-286, 2015 | 3 | 2015 |
| Supervised centrality Cvia sparse network influence regression: an application to the 2021 henan floods' social network Y Ma, W Lan, C Leng, T Li, H Wang arXiv preprint arXiv:2412.18145, 2024 | | 2024 |