高维统计、机器学习、因果推断、成分数据分析、生存分析、统计遗传学与基因组学

1. 国家自然科学基金面上项目，11671018，高维复杂数据的稀疏与低秩建模及推断，2017/01-2020/12，48万元，在研，主持

2. 国家重点研发计划“大气污染成因与控制技术研究”重点专项课题，2016YFC0207703，基于统计与数值模式的多污染物数据场构建，2016/07-2020/06，317.3万元，在研，主持

1.Zhang, J. and Lin, W. (2019). Scalable estimation and regularization for the logistic normal multinomial model. Biometrics, to appear.

2.Cao, Y., Lin, W. and Li, H. (2019). Large covariance estimation for compositional data via composition-adjusted thresholding. Journal of the American Statistical Association, to appear.

3.Cao, Y., Lin, W. and Li, H. (2018). Two-sample tests of high-dimensional means for compositional data. Biometrika, 105, 115-132.

4.Lin, W., Feng, R. and Li, H. (2015). Regularization methods for high-dimensional instrumental variables regression with an application to genetical genomics. Journal of the American Statistical Association, 110, 270-288.

5.Lin, W., Shi, P., Feng, R. and Li, H. (2014). Variable selection in regression with compositional covariates. Biometrika, 101, 785-797.

6.Lin, W. and Lv, J. (2013). High-dimensional sparse additive hazards regression. Journal of the American Statistical Association, 108, 247-264.