1. Quantile regression;
2. Functional data analysis;
3. Spatial data analysis;
4. Model checking.
1. Young Talent Program of Beijing Municipal Commission of Education, 2019;
2. The Rixin Talent Development Program of Beijing University of Technology, 2016.
Publications (since 2017)
1. Ping Yu,Jiang Du, Zhongzhan Zhang*. Varying-coefficient partially functional linear quantile regression models. Journal of the Korean Statistical Society, 2017, 46: 462-475.
2.Jiang Du*, Zhongzhan Zhang, Tianfa Xie. Focused information criterion and model averaging in censored quantile regression. Metrika, 2017, 80: 547-570.
3.Jiang Du*,Xiaoqian Sun, Ruiyuan Cao, Zhongzhan Zhang. Statistical inference for partially linear additive spatial autoregressive models. Spatial Statistics, 2018, 25: 52-67.
4. Jiang Du*, Zhongzhan Zhang, Tianfa Xie. A weighted M-estimator for linear regression models with randomly truncated data. Statistics and Probability Letters, 2018, 138: 90-94.
5.Jiang Du*, Xiuping Chen, Eddy Kwessi, Zhimeng Sun. Model averaging based on rank. Journal of Applied Statistics, 2018, 45: 1900-1919.
6.Jiang Du*, Zhongzhan Zhang, Dengke Xu. Estimation for the censored partially linear quantile regression models. Communications in Statistics-Simulation and Computation, 2018, 8: 2393-2408.
7.Jiang Du, Dengke Xu, Ruiyuan Cao*. Estimation and variable selection for partially functional linear models. Journal of the Korean Statistical Society, 2018,47：436-449.
8.Jiang Du*, Zhongzhan Zhang, Tianfa Xie. Model averaging for M-estimation. Statistics, 2018, 52(6): 1417-1432.
9.Jiang Du,Ruiyuan Cao*, Eddy Kwessi and Zhongzhan Zhang. Estimation for generalized partially functional linear additive regression model. Journal of Applied Statistics, 2019, 46(5): 914-925.
10. Ping Yu,Jiang Du,Zhongzhan Zhang*. Single index partially functional linear regression model. Statistical Papers, 2018, in press.
11.Tianfa Xie, Ruiyuan Cao*,Jiang Du. Variable selection for spatial autoregressive models with a diverging number of parameters. Statistical Papers, 2018, in press.
12.Ruiyuan Cao,Jiang Du*, Jianjun Zhou and Tianfa Xie. FPCA-based Estimation for generalized functional partially linear models. Statistical Papers, 2018, in press.
13.Jiang Du*, Hui Zhao, Zhongzhan Zhang. Dynamic partially functional linear regression model. Statistical Methods & Applications, 2019, 28: 679-693.
14.Longbing Wang, Ruiyuan Cao,Jiang Du, Zhongzhan Zhang. A nonparametric inverse probability weighted estimation for functional data with missing response data at random. Journal of the Korean Statistical Society, 2019, 48: 537-546.
15.Dengke Xu,Jiang Du*.Nonparametric quantile regression estimation for functional data with responses missing at random. Metrika, 2020, in press.
Jiang Du is an associate professor and doctoral supervisor in Beijing University of Technology (BJUT). He obtained his Ph. D. degree in Statistics from BJUT in 2013. He is currently presiding the National Natural Science Foundation of China (No. 111971045), the Science and Technology Project of Beijing Municipal Education Commission (No. KM201910005015), and Young Talent program of Beijing Municipal Commission of Education (No. CIT&TCD201904021).