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 and Model Average Under Generalized Rank Regression. Statistics & Probability letters, 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 Statistics Symposium, 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)