Publications

• Zheng, Z. G., Tong, X. W., & Zhao, H. (2012). Advanced Statistics. Peking University Press.​ ​

• Book chapter：Wu, Q., Zhao, H., Sun, J*. (2020). Variable Selection of Interval-Censored Failure Time Data. In: Bekker, A., Chen,.DG., Ferreira, J.T. (eds). Computational and Methodological Statistics and Biostatistics. Emerging Topics in Statistics and Biostatistics. Springer, Cham. https://doi.org/10.1007/978-3-030-42196-0_20

• Zhao, H., Zhang, Y., & Shao, M. Y. (2025). Decentralized Distributed Sparsity Learning with Expectile Regression. Journal of Systems Science and Mathematical Sciences, 45(12), 3988–4003.

• Zhao, H., Yang, L. Y., & Zheng, R. K. (2025). The Driving Mechanism of Digital Village Construction on the Convergence of Income Gap Between Urban and Rural Residents.​​ Urban Problems, 354(1), 70–84.

• Yuxiang Wu, Mingyue Du, Hui Zhao, Jianguo Sun (2025). Subgroup analysis for high dimensional survival data based on penalized fusion and model averaging. Electronic Journal of Statistics, 19(1):291-313.http://doi.org/10.1214/24-EJS2337

• Lin Luo, Jinzhao Yu, Hui Zhao* (2024). The sparse estimation of the semiparametric linear transformation model with dependent current status data, Journal of Applied Statistics. 51(4): 759-779 (ID: 2161488  http://doi.org/10.1080/02664763.2022.2161488)

• Jinzhao Yu, Daoji Li, Lin Luo, Hui Zhao* (2024). Reproducible learning for accelerated failure time models via deep knockoffs, Communications in Statistics - Theory and Methods. 53(18)：6544-6560. http://doi.org/10.1080/03610926.2023.2247508

• Daoji Li, Jinzhao Yu, Hui Zhao* (2023). CoxKnockoff : Controlled feature selection for the Cox model using knockoffs, Stat.12, e607. http://doi.org/10.1002/sta4.607

• Lei Ge, Jaihee Choi, Hui Zhao, Jianguo Sun (2023). Regression analysis of mixed panel count data with dependent observation processes, Journal of Nonparametric Statistics.35(4):669-684. http://doi.org/10.1080/10485252.2023.2203275

• Yuxiang Wu, Hui Zhao, Jianguo Sun (2023). Group variable selection for Cox model with Interval-censored Failure Time Data, Biometrics. 79(4): 3082-3095.

• Qingkai Dong, Binxia Liu, Hui Zhao* (2023). Weighted least squares model averaging for accelerated failure time models, Computational Statistics and Data Analysis.Vol 184: 107743. http://doi.org/10.1016/j.csda.2023.107743

• Binxia Liu, Hui Zhao, Chunjie Wang. (2023). Bayesian empirical likelihood of linear regression model with current status data, Communications in Statistics - Theory and Methods, 52(20): 7323-7333. Published online: 24 Mar 2022. DOI: 10.1080/03610926.2022.2044491

• Lin Luo, Hui Zhao*. (2023). A new approach to regression analysis of linear transformation model with interval-censored data, Communications in Statistics - Theory and Methods. 52(15): 5470-5482. https://doi.org/10.1080/03610926.2021.2012195

• Zhao, H., Liu, B. X., Dong, Q. K., Zhang, X. Y. (2023). Jackknife model averaging for current status data under the accelerated failure time model.​Acta Mathematicae Applicatae Sinica, 46(3), 313–328.

• Zhao, H., Yu, J. Z. (2023). Dimension reduction for current status data under the additive risk model.​​ Journal of Applied Statistics and Management, 42(3), 439–448.

• Zhao, H., Dong, Q. K. (2022). Variable selection for current status data under the additive risk model.​​ Systems Science and Mathematics. 42(5): 1314-1329. DOI: 10.12341/jssms21468.

• Mingyue Du, Hui Zhao*, Jianguo Sun. (2021). A unified approach to variable selection for Cox’s proportional hazards model with interval-censored failure time data. Statistical Methods in Medical Research,30(8),1833-1849.https://doi.org/10.1177/09622802211009259.

• Dayu Sun, Hui Zhao*, Jianguo Sun. (2021). Regression Analysis of Asynchronous Longitudinal Data with Informative Observation Processes, Computational Statistics & Data Analysis,157, 107161. https://doi.org/10.1016/j.csda.2020.107161.

• Lin Luo, Hui Zhao*. (2021). Robust regression analysis for Clustered Interval-Censored failure time data, Journal of Systems Science and Complexity,34:1156–1174.

• Qiwei Wu, Hui Zhao*, Liang Zhu, Jianguo Sun. (2020). Variable selection for high-dimensional partly linear additive Cox model with application to Alzheimer’s disease, Statistics in Medicine.39(23), 3120-3134. DOI:10.1002/sim.8594.

• Hui Zhao, Qiwei Wu, Peter B. Gilbert, Ying Q.Chen, Jianguo Sun, (2020). A regularized estimation approach for case-cohort periodic follow-up studies with an application to HIV vaccine trials, Biometrical Journal, 62,1176–1191. DOI:10.1002/bimj.201900180.

• Hui Zhao, Qiwei Wu, Gang Li, Jianguo Sun. (2020). Simultaneous estimation and variable selection for interval-censored data with broken adaptive ridge regression. Journal of the American Statistical Association. 115(529), 204-216. DOI: 10.1080/01621459.2018.1537922.

• Qin Jiang, Hui Zhao, Hong Qin. (2019). On a general class of semiparametric hazards regression models for recurrent gap times, Acta Mathematicae Applicatae Sinica, English Series, 35 (3):549-563.

• Zhao, H., Cui, Q., Sun, J. G. (2019). A Copula model approach for the additive hazards model with dependent current status data. Science China Mathematics, ​49(9), 1261–1272.

• Hui Zhao, Dayu Sun, Gang Li, Jianguo Sun.(2019).Simultaneous Estimation and Variable Selection for Incomplete Event History Studies. Journal of Multivariate Analysis,171,350-361.

• Guanglei Yu, Yang Li, Liang Zhu, Hui Zhao*, Jianguo Sun. (2019). An Additive-Multiplicative Means Model for Panel Count Data with Dependent Observation and Drop-out processes. Scandinavian Journal of Statistics, 46(2), 414-431. DOI:10.1111/sjos.12357.

• Hui Zhao, Dayu Sun, Gang Li, Jianguo Sun. (2018). Variable selection for the recurrent event data with broken adaptive ridge regression. The Canadian Journal  of  Statistics. 46 (3): 416–428.

• Hui Zhao, Chenchen Ma, Junlong Li, Jianguo Sun. (2018). Regression Analysis of Clustered Interval-Censored Failure Time Data with Linear Transformation Models in the Presence of Informative Cluster Size. Journal of  Nonparametric Statistics. 30 (3): 703–715.

• Qi Cui, Hui Zhao, Jianguo Sun. (2018). Semiparametric regression analysis of dependent current status data based on copula. Statistics and its interface. 11(3):463-471.

• Peijie Wang, Hui Zhao*, Jianguo Sun. (2018). Inference on semiparametric transformation model with general interval-censored failure time data. Journal of  Nonparametric Statistics. 30 (3): 758-773.

• Da Xu, Hui Zhao, Jianguo Sun. (2018). Joint analysis of interval-censored failure time data and panel count data, Lifetime Data Analysis. 24(1):94-109.

• Peijie Wang, Hui Zhao, Jianguo Sun. (2016). Regression analysis of case k interval-censored failure time data in the presence of informative censoring.  Biometrics,72,1103-1112.

• Liang Zhu, Hui Zhao*, Jianguo Sun, Wendy Leisenring, Leslie L. Robison. (2015). Regression analysis of mixed recurrent-event and panel-count data with additive rate models. Biometrics, 71,71-79.

• Jianguo Sun, Yanqin Feng, Hui Zhao. (2015). Simple estimation procedures for regression analysis of interval-censored failure time data under the proportional hazards model. Lifetime Data Analysis, 21(1),138-55.

• Yang Li, Hui Zhao*, Jianguo Sun,(2014). Nonparametric tests for panel count data with unequal observation processes. Computational Statistics and Data Analysis, 73, 103-111. (SCI)

• Hui Zhao, Kate Virkler, Jianguo Sun,(2014). Nonparametric comparison for multivariate panel count data.  Communications in Statistics - Theory and Methods. Vol. 43(3), 644-655.(SCI)

• Liang Zhu, Hui Zhao, Jianguo Sun, Stanley Pounds. (2014). A conditional approach for regression analysis of longitudinal data with informative observation time and non-negligible observation duration, Communications in Statistics - Theory and Methods. 43, 4998-5011.(SCI)

• Haixiang Zhang, Hui Zhao*, Jianguo Sun, Dehui Wang,(2013)..Regression analysis of multivariate panel count data with informative observation process. Journal of Multivariate Analysis. 119, 71-80.(SCI)

• Hui Zhao, Yang Li, Jianguo Sun, (2013). Analyzing panel count data with dependent observation process and a terminal event.  The Canadian Journal of Statistics, 41, 174-191.(SCI)

• Liang Zhu, Hui Zhao*, Jianguo Sun, Pounds Stanley, (2013). Joint analysis of longitudinal data and recurrent episodes data with application to medical cost analysis, Biometrical Journal, 55,5-16.(SCI)

• Hui Zhao, Yang Li, Jianguo Sun, (2013). Semiparametric analysis of multivariate panel count data with dependent observation process and terminal event. Journal of  Nonparametric Statistics,  25, 379-394.(SCI)

• Hui Zhao, Jie Zhou, Liuquan Sun, (2013). A marginal additive rates model for recurrent event data with a terminal event. Communications in Statistics - Theory and Methods, 42,2567-2583.(SCI)

• Ni Li, Hui Zhao, Jianguo Sun, (2013). Semiparametric transformation models for panel count data with correlated observation and follow-up times, Statistics in Medicine, 32, 3039–3054.(SCI)

• Liang Zhu, Xingwei Tong, Hui Zhao, Jianguo Sun, Deo Kumar Srivastava, Wendy Leisenring, Leslie L. Robison, (2013). Statistical analysis of mixed recurrent event data with application to cancer survivor study, Statistics in Medicine, 32(11),1954-1963.(SCI)

• Hui Zhao, Ningning Jiang, (2012). A two-stage estimation algorithm for a type of current status data. Journal of Systems Science and Complexity, 25, 556-566.(SCI)

• Hui Zhao, Dan Yu, (2009). A random effects generalized linear model for reliability compositive evaluation. Science in China (A), 52, 2218-2227.

• Hui Zhao, Zhongguo Zheng, Baijun Liu, (2005). On the Markov equivalence of maximal ancestral graphs. Science in China (A),48(4),548-562.

• Baijun Liu, Zhongguo Zheng, Hui Zhao, (2005). An efficient algorithm for finding the largest chain graph given chain graph. Science in China (A), 48(11), 517-1530.

• Xingwei Tong, Hengjian Cui, Hui Zhao, (2005). Asymptotics of Huber-Dutter estimators for partial linear model with nonstochastic designs. Acta Mathematicae Applicatae Sinica, 21,257-268.

• Hui Zhao, Zhongguo Zheng, Jing Xu, (2006). Causal inference in the models with hidden variables and selection bias.  Acta Scientiarum naturalium Universitatis Pekinensis, 42, 584-589.(EI)

• Hui Zhao, Zhongguo Zheng (2008). Comparing identifiability criteria for causal effects in Gaussian causal models , Acta Mathematica Scientia, 28,808-817.

• Hui Zhao, Zhongguo Zheng (2007). Graphical Model and Its Application s in Statistical Modelling, Journal of Applied Statistics and Management, 26(3): 741-746.

• Hui Zhao, Zhongguo Zheng (2007). Causal Analysis for the Efficacy of a Type of Chinese Medicine - Jiangzhiling Tablet, Journal of Applied Statistics and Management, 26(4): 427-431.

• Hui Zhao, Ming Xiao, The Application of Bagging to Hybrid Adaptive Splines, Chinese Journal of applied probability and statistics, 21,278-284.