Hanzhong Liu
Associate Professor
Research Areas: high dimensional statistical inference, causal inference
Office: Room 212-B, Weiqing Building, Tsinghua University
Phone: +86-10-62780575
Email: lhz2016@tsinghua.edu.cn
BACKGROUND
- Ph.D in Statistics, Peking University
- Visiting Student, Department of Statistics, University of California at Berkeley
- Postdoctoral Scholar, Department of Statistics, University of California at Berkeley
PUBLICATIONS
- Liu, H., Xu, X., & J. J. Li (2020). A bootstrap Lasso + Partial Ridge method to construct confidence intervals for parameters in high-dimensional sparse linear models. Statistica Sinica, 30, 1333-1355.
- Liu, H., & Yang, Y. (2019). Regression-adjusted average treatment effect estimates in stratified randomized experiments. Biometrika.
- Liu, H., & Yu, B. (2017). Comments on: High-dimensional simultaneous inference with the bootstrap. Test, 26(4), 740-750.
- Bloniarz, A., Liu, H., Zhang, C. H., Sekhon, J. S., & Yu, B. (2016). Lasso adjustments of treatment effect estimates in randomized experiments. Proceedings of the National Academy of Sciences, 113(27), 7383-7390.
- Wu, L., Yang, Y., & Liu, H. (2014). Nonnegative-lasso and application in index tracking. Computational Statistics & Data Analysis, 70, 116-126.
- Liu, H., & Yu, B. (2013). Asymptotic properties of Lasso+ mLS and Lasso+ Ridge in sparse high-dimensional linear regression. Electronic Journal of Statistics, 7, 3124-3169.