张庆昭
副教授
中科院概率与数理统计博士
电话：
电子邮件：qzzhang at xmu.edu.cn
办公室：经济楼B503
Office Hours:每周一上午9:30-11:30


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 andThe 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 Associateat 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


Wu, C., Zhang, Q., Jiang, Y. and Ma, S.*(2018). Robust Network-based Analysis of the Associations between (Epi)Genetic Measurements. Journal of Multivariate Analysis, 168, 119-130.
Fang, K., Fan, X., Zhang, Q. and Ma, S.*(2018). Integrative Sparse Principal Component Analysis. Journal of Multivariate Analysis, 166, 1-16.
Bao, F., Deng, Y., Du, M., Ren, Z., Zhang, Q., Zhao, Y., Suo, J., Zhang, Z., Wang, M.* and Dai, Q. (2018) Probabilistic natural mapping of gene-level tests for genome-wide association studies. Briefings in Bioinformatics, 19(4), 545-553.
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.
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.
Zhang, Q., Duan, X. and Ma, S.* (2017). Focused Information Criterion andModel Average Under Generalized Rank Regression. Statistics & Probabilityletters, 122, 11-19.
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.
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.

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.

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.

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.

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.

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.

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.

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.

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 StatisticsSymposium, Springer.

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.

Zhang, T., Zhang, Q. and Wang, Q.* (2014). Model detection for functional polynomial regression.Computational Statistics & Data Analysis, 70, 183-197.

Zhang, Q., Li, D.* and Wang, H. (2013). A note on tail dependence regression.Journal of Multivariate Analysis, 120, 163-172.

Zhang, Q. and Wang, Q.* (2013). Local least absolute relative error estimating approach for partially linear multiplicative model.Statistica Sinica, 23, 1091-1116.

（* 通讯作者）


多源高维数据的整合分析方法与理论，国家自然科学面上基金（**）， 2020.01-2023.12
带顺序结构的高维交互效应模型的稳健推断方法，教育部人文社会科学研究青年基金 （19YJC910010），2019-2021 高维异质多数据集整合方法研究，中央高校业务费（）， 2017.01-2019.12 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（**），2015.01-2017.12 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