张庆昭

副教授

中科院概率与数理统计博士


电话:0592-2180502

电子邮件:qzzhang@xmu.edu.cn

办公室:经济楼B503

个人简介 研究成果 研究项目

工作经历
Associate Professor at  Department of Statistics, School of Economics and The Wang Yanan Institute for Studies in Economics, September 2016-

Postdoctoral Associate at Yale School of Public Health, Department of Biostatistics, August 2015-August 2016
Research Assistant at Department of Applied Mathematics, The HongKong Polytechnic University, July 2015
Postdoctoral Associate at School of Mathematics, University of Chinese Academy of Sciences, June 2013-September 2016
 
 
教育背景
Ph.D. in Probability and Mathematical Statistics, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, 2008-2013; 
B.S. in Mathematics and Applied Mathematics, Huazhong University of Science & Technology, 2004-2008
 
研究兴趣
Semiparametrics, High-dimensional data analysis, Empirical likelihood, Robust statistics, Statistical Machine Learning.
 
教学
Advanced Probability Theory, Multivariate Analysis

 

  1. Huang, Y., Zhang, Q., Zhang, S., Huang, J. and Ma, S.* (2017) Promoting similarity of sparsity structures in integrative analysis with penalization. Journal of the American Statistical Association, 112, 342-350.
  2. Sun, Z., Chen, F., Zhou, X. and Zhang, Q.* (2017). Improved model checking methods for parametric models with responses missing at random. Journal of Multivariate Analysis, 154, 147-161.
  3. Zhang, Q., Duan, X. and Ma, S.* (2017). Focused Information Criterion and Model Average Under Generalized Rank Regression. Statistics & Probability letters, 122, 11-19.
  4. Li, Y., Zhang, Q. and Wang, Q.* (2017). Penalized estimation equation for an extended single-index model. Annals of the Institute of Statistical Mathematics, 69, 169--187.
  5. Wang, G., Zhao, Y., Zhang, Q., Zang, Y., Zhang, S. and Ma, S.*(2017). Identifying gene-environment interactions associated with prognosis using penalized robust regression. Invited book chapter. Big and Complex Data Analysis: Statistical Methodologies and Applications, Springer, 347-367.
  6. Zang, Y.,Zhang, Q., Zhang, S., Li, Q. and Ma, S.*(2017). Tests for High Dimensional General linear Regression Model. Invited book chapter. Big and Complex Data Analysis:Statistical Methodologies and Applications, Springer, 29-50.
  7. Zang, Y., Zhang, S., Li, Q. and Zhang, Q.* (2016). Jackknife empirical likelihood test for high-dimensional regression coefficients.  Computational Statistics & Data Analysis, 94, 302-316.
  8. Lai, P., Zhang, Q.*, Lian, H. and Wang, Q. (2016). Efficient estimation for the heteroscedastic single-index varying coefficient models. Statistics & Probability letters, 110, 84-93.
  9. Wu, X., Zhang, S., Zhang, Q. and Ma, S.* (2016). Detecting change point in linear regression using jackknife empirical likelihood. Statistics and Its Interface, 9, 113-122.
  10. Wu, X., Zhang, Q. and Zhang, S.* (2016). Detecting difference between coefficients in linear model Using Jackknife Empirical Likelihood. Journal of Systems Science and Complexity, English Series, 29, 542-556.
  11. Zhang, T., Zhang, Q.* and Li, N. (2016). Least absolute relative error estimation for functional quadratic multiplicative model. Communications in Statistics-Theory and Methods, 45, 5802-5817.
  12. Zhang, Q., Zhang, S., Liu, J., Huang, J. and Ma, S.* (2016). Penalized integrative analysis under the accelerated failure time model.  Statistica Sinica, 26, 493-508.
  13. Zang, Y., Zhao, Y., Zhang, Q., Chai, H., Zhang, S. and Ma, S.*(2015). Identifying Gene-Environment Interactions with A Least Relative Error Approach.Book chapter,ICSA book series in statistics, 305-322, 2015 ICSA/Graybill Applied Statistics Symposium, Springer.
  14. Dai, P., Zhang, Q. and Sun, Z.* (2014). Variable selection of generalized regression models based on maximum rank correlation. Acta Mathematicae Applicatae Sinica, English Series, 30, 833-844.
  15. Zhang, T., Zhang, Q. and Wang, Q.* (2014). Model detection for functional polynomial regression. Computational Statistics & Data Analysis, 70, 183-197.
  16. Zhang, Q., Li, D.* and Wang, H. (2013). A note on tail dependence regression. Journal of Multivariate Analysis, 120, 163-172.
  17. Zhang, Q. and Wang, Q.* (2013). Local least absolute relative error estimating approach for partially linear multiplicative model. Statistica Sinica, 23, 1091-1116.
  18. (* 通讯作者)
  1.  基于分位数回归的高维数据降维及变量选择研究,国家自然科学青年基金(11401561),2015.01-2017.12
  2. 基于中心分位数子空间的充分降维问题研究,中国博士后科学基金二等资助(2014M550799),2014.03-2016.06