General
Qingzhao Zhang  
Email: qzzhang@ucas.ac.cn
Address:  School of Mathematical Sciences, University of Chinese Academy of Sciences, No. 19A Yuquan Road, Beijing, China
Postcode: 100049

Research Areas

Semi/Non-paprametric statistics, High dimensional analysis, Variable selection, Dimension Reduction, Functional data analysis, Statistical learning

Education

Sep. 2008 - June 2013 Ph.D. in Probability and Statistics at Academy of Mathematics and Systems Science, Chinese Academy of Sciences
Advisor: Prof. Qi-hua Wang 

Sep. 2004 - June 2008  B.S. in Mathematics and Applied Mathematics, School of Mathematics, Huazhong University of Science and Technology

Experience

   
Work Experience
June 2013 - present
School of Mathematical Sciences, University of Chinese Academy of Sciences
Teaching Experience
Linear regression analysis and its applications

Publications

   
Papers
  • Tao Zhang, Qingzhao Zhang* and Naixiong Li(2014). Least absolute relative error estimation for functional quadratic multiplicative model. To appear at Communications in Statistics - Theory and Methods.
  • Xinqi Wu, Qingzhao Zhang and Sanguo Zhang*(2014). Detecting di erence between coecients in linear model Using Jackknife Empirical Likelihood. To appear at Journal of Systems Science and Complexity.
  • Pengjie Dai, Qingzhao Zhang and Zhihua Sun*(2014). Variable selection of generalized regression models based on maximum rank correlation. To appear at Acta Mathematicae Applicatae Sinica, English Series.
  • Tao Zhang, Qingzhao Zhang and QihuaWang*(2014). Model detection for functional polynomial regression. Computational Statistics & Data Analysis, 70, 183-197.
  • Qingzhao Zhang, Deyuan Li* and HanshengWang(2013). A Note on Tail Dependence Regression. Journal of Multivariate Analysis, 120, 163-172.
  • Qingzhao Zhang and Qihua Wang*(2013). Local least absolute relative error estimating approach for partially linear multiplicative model. Statistica Sinica, 23, 1091-1116.

Conferences


  1. "Jackknife Empirical Likelihood Test for High-dimensional Regreesion Coefficients", Invited talk at Third International Symposium on Biostatistics at Chengdu, China. June 27-28, 2014.
    2.         
  2. "Sufficient dimension reduction through central quantile subspaces", Invited talk at 2014 Symposium on Applied Statistics at Capital Normal University. June 7-8, 2014.