Name: XIE Tianfa

Academic Title: Associate Professor

Course：BDIC2005J Probability and Statistics

Email: xietf@bjut.edu.cn

Educational background:

2002-2005 Ph.D. in Probability and Statistics, Academy of Mathematics & Systems Science, Chinese Academy of Sciences, China

1999- 2002   M. Sc. in Applied Statistics, Beijing University of Technology, China

   1995- 1999 B. Sc. in Mathematics, Soochow University, China

Working experience:

2008.6-Present Beijing University of Technology, Lecturer, Associate Professor

   2005.7-2008.5 Beijing Institute of Technology, Lecturer

Membership of Academic Associations:

Reviewer of “Mathematical Review”

Member of ISO/TC69

Vice Secretary and Member of SAC/TC21

 

Research interests:

Robust statistics (especially statistical data depth), Model Checking, Statistical Modeling and Analysis for Complex Data, Applied Statistics and its Standardization

 

Research projects:

2020.1-2022.12 Beijing Natural Science Foundation（1202001）

Science and Technology Project of Beijing Municipal Education Commission No. KM201710005032

2017.6-2021.6 NQI project No. 2017YFF0209004

Awards:

2005: “Zhong Jiaqing” Prize for the excellent paper of Probabilities and Statistics meeting of Young People in Beijing and Tianjin；

2014: China Innovation Works of Standards (Rank 2)

 

Major Publications:

[1] Tianfa Xie, Ruiyuan Cao, Ping Yu. Rank-based test for partial functional linear regression models, Journal of Systems Sciences and Complexity. in press

DOI: 10.1007/s11424-020-8362-2

[2] Miaomiao Wang, Chunling Liu, Tianfa Xie, zhihua sun. Data-driven model check for errors-in-variables varying coefficient models with replicate measurements, accepted by Computational Statistics and Data Analysis. 2020, 141: 12–27.

[3] Xie Tianfa, Cao Ruiyuan and Du, Jiang. Variable selection for spatial autoregressive models with a diverging number of parameters, Stat Papers (2018). https://doi.org/10.1007/s00362-018-0984-2

[4] Jiang Du, Zhongzhan Zhang, Tianfa Xie. A weighted M-estimator for linear regression models with randomly truncated data, Statistics and Probability Letters. 2018, V138, 90-94.

[5] Wang Yafei, Tianfa Xie, Zhongzhan Zhang. Partial functional linear models with ARCH errors, Open Journal of Statistics. 2018, 8(2): 345-361

[6] Jiang Du, Zhongzhan Zhang, Tianfa Xie. Focused information criterion and model averaging in censored quantile regression, Metrika, 2017, Volume 80, Issue 5, 547–570.

[7] Tianfa Xie, Zhihua Sun and Liuquan Sun, A consistent model specification test for a partial linear model with missing covariates at random, Journal of Nonparametric Statistics, 2012，24 (4), 841-856.

[8] Sun Z H, Xie T F, Liang H. Statistical inference for right-censored data with nonignorable missing censoring indicators. Sci China Math, 2013, 56: 1263–1278.

[9] Jiang Du, Zhimeng Sun and Tianfa Xie, M-estimation for the partially linear regression model under monotonic constraints, Statistics & Probability Letters, 2013, 83 (5), 1353–1363.

[10] Tianfa Xie, Wenxing Ding. Statistical Issues on Optimization for Software Metric Models with Missing Data, Proceedings of 9th International Conference on Natural Computation 2013: 1150-1154.

[11] Jiang Du, Zhongzhan Zhang and Tianfa Xie, Variable Selection for Semiparametric Isotonic Regression Models, International Journal of Intelligent Technologies and Applied Statistics, 2011, 4(4), 503-518.

[12] T.F. Xie and G.Y. Li (2010), Large sample and robust properties of -median, Journal of Systems Science and Complexity，23: 1133-1142.

 [13] T.F. Xie and W. E. Wong (2010), An Improved Method to Simplify Software Metric Models  

 Constructed with Incomplete Data Samples, in Proceedings of Fuzzy Systems and knowledge discovery

 2010, 1682-1688.

 [14] Project Leader of “ISO/TR 20693 Statistical methods for implementation of Six Sigma-Selected  

 illustrations of distribution identification studies” released on the May of 2019 by ISO.