正高

李高荣

个人信息简介

姓名:李高荣 职称:教授,博士生导师

北京师范大学第十二届“最受本科生欢迎的十佳教师”。

主要研究方向:高维统计、非参数统计和复杂数据分析、模型和变量选择、统计学习、因果推断、纵向数据分析、测量误差和经验似然等。

联系方式: ligaorong@bnu.edu.cn; ligaorong@gmail.com

科研项目

1. 国家自然科学基金:高维噪声数据的有效和稳健统计方法、理论及其应用(No: 12271046),2023年1月-2026年12月,主持。

2. 国家自然科学基金重点项目:因果分析的若干统计学基础问题的研究及其应用 (No: 12131006),2022年1月-2026年12月,排名第二参与。

3. 国家自然科学基金:高维回归模型的大规模统计学习和推断 (No: 11871001),2019年1月-2022年12月,主持。

4. 国家自然科学基金:不完全数据下半参数混合效应模型的研究 (No: 11971001),2020年1月-2023年12月,排名第二参与。

5. 中央高校基本科研业务费专项资金资助:高维半参数因果推断模型的统计学习研究(No: 2019NTSS18),2019年9月-2021年9月,主持。

6. 北京市自然科学基金:大规模因果推断模型的统计学习及其应用(No: 1182003),2018年1月-2020年12月,主持。

7. 国家自然科学基金:半参数面板数据交互固定效应模型的理论与应用研究 (No:11471029),2015年1月-2018年12月,主持。

8. 北京市自然科学基金:纵向数据变系数混合效应模型的适应性统计研究及其应用(No: 1142002),2014年1月-2016年12月,主持。

9. 北京市教育委员会科技计划面上项目:函数型数据半参数模型的统计方法、理论及应用(No:KM201410005010),2014年1月-2016年12月,主持。

10.北京市自然科学基金委员会与北京市科学技术研究院联合资助项目: 高维数据的低维非线性逼近方法与应用 (No: L140003),2014年1月-2016年6月,主要参与者。

11.北京工业大学“京华人才”支持计划项目(No:2013-JH-L07),2013年1月-2015年12月,主持。

12.国家自然科学青年基金:纵向数据单指标混合效应模型的有效统计推断 (No:11101014),2012年1月-2014年12月,主持。

13.教育部博士点学科专项科研基金:可加模型的统计推断及应用 (No:20121103110004), 2013年1月-2015年12月,主要参与者。

14.高等学校博士学科点专项科研基金联合资助课题(新教师类):高维数据半参数模型的变量选择及其应用 (No:20101103120016),2011年1月-2013年12月,主持。

15.北京市属高等学校人才强教深化计划“中青年骨干人才培养计划”项目 (No:PHR20110822),2011年1月-2013年12月,主持。

16.北京市优秀人才培养资助项目:半参数混合效应模型的统计推断以及变量选择研究 (No:2010D005015000002),2010年10月-2012年10月,主持。

17.中国博士后科学基金:高维数据半参数模型的统计推断 (No:20080430633),2008年7月-2009年9月,主持。

18.上海市博士后科研资助计划资助:高维数据单指标模型中适应统计方法的研究 (No:08R214121),2008年8月-2009年9月,主持。

代表性论文

1. Li Gaorong, Huang Lei, Yang Jin and Zhang Wenyang* (2022). A Synthetic Regression Model for Large Portfolio Allocation. Journal of Business & Economic Statistics, in press.

2. Feng Sanying, Kong Kaidi, Kong Yinfei, Li Gaorong* and Wang Zhaoliang (2022). Statistical Inference of Heterogeneous Treatment Effect Based on Single-Index Model.  Computational Statistics and Data Analysis, 175: 107554, DOI: 10.1016/j.csda.2022.107554.

3. Wei Shaojie, Li Gaorong, Zhang Zhongzhan (2022). An Alternative Doubly Robust Estimation in Causal Inference Model.  Communications in Mathematics and Statistics , in press. DOI: 10.1007/s40304-022-00308-4

4. Yuan Panxu, Feng Sanying, Li Gaorong* (2022). Revisiting Feature Selection for Linear Models with FDR and Power Guarantees.  Journal of the Korean Statistical Society,  in press. DOI: 10.1007/s42952-022-00179-z

5. Wei Shaojie, Zhang Zhongzhan* and Li Gaorong (2022). Estimation of the Average Treatment Effect on the Treated with Misclassified Binary Outcome.  Stat , 11(1): e422.

6. Liu Jiamin, Li Gaorong, Zhang Jianqiang and Xu Wangli* (2022). Symmetrical Independence Tests for Two Random Vectors with Arbitrary Dimensional Graphs.  Acta Mathematica Sinica, English Series , 38(4): 662-682.

7. Feng Sanying, Li Gaorong*, Peng Heng and Tong Tiejun (2021). Varying-Coefficient Panel Data Models with Interactive Fixed Effects.  Statistica Sinica , 31: 935-957.

8. Feng Sanying, Tian Ping, Hu Yuping* and Li Gaorong (2021). Estimation in Functional Single-Index Varying Coefficient Model. Journal of Statistical Planning and Inference , 214: 62-75.

9. Fan Yingying, Demirkaya Emre, Li Gaorong and Lv Jinchi (2020). RANK: Large-Scale Inference with Graphical Nonlinear Knockoffs.  Journal of the American Statistical Association,  115(529): 362-379.

10. Feng Sanying, Li Gaorong*, Tong Tiejun and Luo Shuanghua (2020). Testing for Heteroskedasticity in Two-Way Fixed Effects Panel Data Models.  Journal of Applied Statistics, 47(1): 91-116.

11. Chen Ranran, Li Gaorong* and Feng Sanying (2020). Testing for Covariance Matrices in Time-Varying Coefficient Panel Data Models with Fixed Effects.  Journal of the Korean Statistical Society,  49: 82-116.

12. Zhang Jun, Yang Yiping, Li Gaorong* (2020). Logarithmic Calibration for Multiplicative Distortion Measurement Errors Regression Models.  Statistica Neerlandica , 74: 462-488.

13. 何胜美,李高荣,许王莉* (2020). 基于秩能量距离的超高维特征筛选研究.  统计研究 ,37(8): 117-128。

14. Yue Lili, Li Gaorong* and Lian Heng (2019). Identification and Estimation in Quantile Varying-Coefficient Models with Unknown Link Function.  Test , 28(4): 1251-1275.

15. Yue Lili, Li Gaorong*, Lian Heng and Wan Xiang (2019). Regression Adjustment for Treatment Effect with Multicollinearity in High Dimensions.  Computational Statistics and Data Analysis,  134: 17-35.

16. Zhang Shen, Zhao Peixin*, Li Gaorong and Xu Wangli (2019). Nonparametric Independence Screening for Ultra-high Dimensional Generalized Varying Coefficient Models with Longitudinal Data.  Journal of Multivariate Analysis,  171: 37-52 .

17. Zhang Jun, Niu Cuizhen, Li Gaorong (2019). Exploring the Constant Coefficient of a Single-Index Variation.  Brazilian Journal of Probability and Statistics , 33(1): 57-86.

18. Yang Yiping, Tong Tiejun and Li Gaorong* (2019). SIMEX Estimation for Single-Index Model with Covariate Measurement Error.  AStA Advances in Statistical Analysis , 103:137-161. (The paper has been recognized as a highly cited paper in ISI Web of Science)

19. Zhang Jun, Lin Bingqing* and Li Gaorong (2019). Nonlinear Regression Models with General Distortion Measurement Errors.  Journal of Statistical Computation and Simulation , 89(8): 1482-1504.

20. Wang Zhaoliang, Xue Liugen, Li Gaorong and Lu Fei (2019). Spline Estimator for Ultra-high Dimensional Partially Linear Varying Coefficient Models.  Annals of the Institute of Statistical Mathematics , 71: 657-677.

21. 夏强, 梁茹冰, 李高荣* (2019). 参数单指标分位数自回归模型的诊断检验.  中国科学  :   数学 , 49: 879-898.

22. Cheng Ming-Yen*, Feng Sanying, Li Gaorong and Lian Heng (2018). Greedy Forward Regression for Variable Screening.  Australian & New Zealand Journal of Statistics , 60(1): 20-42.

23. Zheng Zemin, Li Yang, Yu Chongxiu and Li Gaorong* (2018). Balanced Estimation for High-dimensional Measurement Error Models.  Computational Statistics and Data Analysis , 126: 78-91.

24. Guo Xu, Li Gaorong, McAleer Michael, Wong Wing-Keung* (2018). Specification Testing of Production in a Stochastic Frontier Model.  Sustainability , 10, 3082, pp1-10. DOI: 10.3390/su10093082.

25. Zhou Yan, Zhang Baoxue, Li Gaorong, Tong Tiejun and Wan Xiang* (2017). GD-RDA: A New Regularized Discriminant Analysis for High Dimensional Data.  Journal of Computational Biology , 24: 1099-1111.

26. Li Yujie, Li Gaorong*, Lian Heng and Tong Tiejun (2017). Profile Forward Regression Screening for Ultra-High Dimensional Semiparametric Varying Coefficient Partially Linear Models.  Journal of Multivariate Analysis , 155: 133-150.

27. 岳莉莉, 史建红*,李高荣 (2017). 含有测量误差的 Panel 数据模型的统计推断.  中国科学:数学 , 47(9): 1077-1088.

28. Yang Yiping, Li Gaorong* and Lian Heng (2016). Nonconcave Penalized Estimation in Partially Linear Models with Longitudinal Data.  Statistics,  50(1): 43-59.

29. Li Gaorong, Lai Peng and Lian Heng* (2015). Variable Selection and Estimation for Partially Linear Single-index Models with Longitudinal Data.  Statistics and Computing , 25(3): 579-593.

30. Li Gaorong, Lian Heng, Lai Peng and Peng Heng* (2015). Variable Selection for Fixed Effects Varying Coefficient Models. Acta Mathematica Sinica  ,   English Series  ,  31(1):91-110.

31. Zhang Jun*, Li Gaorong and Feng Zhenghui (2015). Checking the Adequacy for A Distortion Errors-In-Variables Parametric Regression Model.  Computational Statistics and Data Analysis , 83: 52-64.

32. Yang Yiping, Li Gaorong* and Tong Tiejun (2015). Corrected Empirical Likelihood for a Class of Generalized Linear Measurement Error Models.  SCIENCE CHINA Mathematics , 58(7): 1523-1536.

33. Li Gaorong, Peng Heng*, Dong Kai and Tong Tiejun (2014). Simultaneous Confidence Bands and Hypothesis Testing in Single-index Models.  Statistica Sinica, 24: 937-955.

34. Yang Yiping, Li Gaorong and Peng Heng* (2014). Empirical Likelihood for Varying Coefficient Errors-in-Variables Models with Longitudinal Data.  Journal of Multivariate Analysis , 127: 1-18.

35. Lian Heng* and Li Gaorong (2014). Series Expansion for Functional Sufficient Dimension Reduction.  Journal of Multivariate Analysis,  124: 150-165.

36. Li Gaorong*, Lian Heng, Feng Sanying and Zhu Lixing (2013). Automatic Variable Selection for Longitudinal Generalized Linear Models.  Computational Statistics and Data Analysis , 61: 174-186.

37. Lai Peng, Li Gaorong and Lian Heng* (2013). Quadratic Inference Functions for Partially Linear Single-Index Models with Longitudinal Data.  Journal of Multivariate Analysis , 118: 115-127.

38. Li Gaorong*, Peng Heng and Tong Tiejun (2013). Simultaneous Confidence Band for Nonparametric Fixed-Effects Panel Data Models.  Economics Letters , 119: 229-232.

39. Li Gaorong*, Peng Heng, Zhang Jun and Zhu Lixing (2012). Robust Rank Correlation Based Screening.  Annals of Statistics , 40(3): 1846-1877. (The paper had been recognized as a highly cited paper from 2013 to present in ISI Web of Science.)

40. Li Gaorong, Lin Lu and Zhu Lixing* (2012).  Empirical Likelihood for Varying Coefficient Partially Linear Model with Diverging Number of Parameters.  Journal of Multivariate Analysis,  105: 85-111.

41. Zhang Weiwei, Li Gaorong* and Xue Liugen (2011). Profile Inference on Partially Linear Varying-Coefficient Errors-in-Variables Models under Restricted Condition.  Computational Statistics and Data Analysis , 55: 3027-3040.

42. Li Gaorong, Xue Liugen and Lian Heng* (2011). Semi-varying Coefficient Models with a Diverging Number of Components. Journal of Multivariate Analysis , 102: 1166-1174.

43. Li Gaorong, Feng Sanying and Peng Heng* (2011). A Profile-type Smoothed Score Function for a Varying Coefficient Partially Linear Model.  Journal of Multivariate Analysis, 102: 372-385 .

44. Li Gaorong, Peng Heng* and Zhu Lixing (2011). Nonconcave Penalized M-estimation with a Diverging Number of Parameters.  Statistica Sinica,  21: 391-419.

45. Li Gaorong, Zhu Liping* and Zhu Lixing (2010). Adaptive Confidence Region for the Direction in Semiparametric Regressions.  Journal of Multivariate Analysis , 101: 1364-1377.

46. Li Gaorong, Zhu Lixing*, Xue Liugen and Feng Sanying (2010). Empirical Likelihood Inference in Partially Linear Single-index Models for Longitudinal Data.  Journal of Multivariate Analysis , 101: 718-732.

47. Zhu Lixing, Lin Lu, Cui Xia and Li Gaorong (2010). Bias-corrected Empirical Likelihood in a Multi-link Semiparametric Model.  Journal of Multivariate Analysis , 101: 850-868.

48. Li Gaorong*, Tian Ping and Xue Liugen (2008). Generalized Empirical Likelihood Inference in Semiparametric Regression Model for Longitudinal Data .  Acta Mathematica Sinica  ,   English Series ,24(12): 2029-2040.

专著和教材

1. 李高荣,杨宜平(2015). 纵向数据半参数模型. 北京:科学出版社.

2. 李高荣,张君,冯三营(2016). 现代测量误差模型. 北京:科学出版社. (现代数学基础丛书,162)

3. 李高荣,吴密霞 (2021). 多元统计分析. 北京:科学出版社. (统计与数据科学丛书,4)