快捷导航：
研究方向
教育背景
工作经历
教学工作
科研工作
主要荣誉
学术兼职
其它
发表论文

张海祥 职称：
副教授
院系：
应用数学中心
电子邮箱：
haixiang.zhang@tju.edu.cn
办公地点：
卫津路校区25教



研究方向 高维数据；生物统计；时间序列分析
教育背景 2003.09 - 2007.07 吉林大学 学士
2007.09 - 2009.07 吉林大学 硕士
2009.09 - 2012.12 吉林大学 博士
2011.09 - 2012.09 美国密苏里大学 国家公派联合培养博士生
工作经历 2013.04 - 2016.11 吉林大学数学学院 讲师
2013.05 - 2015.05 中国科学院数学与系统科学研究院 博士后
2015.05 - 2016.05 美国西北大学 博士后
2016.12 - 今 天津大学应用数学中心 副教授
教学工作 学生指导 指导硕士生 2人 (在读)，博士生0人
竞赛指导 数学竞赛、数学建模获奖情况
教改项目 (只填写省部级以上的) 身份
科研工作 基金项目 身份
2014.05-2015.05 中国博士后科学基金(面板计数数据的统计推断) 主持人
2014.01-2016.12 国家自然科学基金(多元线性整值时间序列的统计分析) 主持人
主要荣誉 吉林省自然科学学术成果奖 (2012)；
第十一届全国统计科研优秀成果奖(2013);
教育部自然科学二等奖(2016).

学术兼职 无
其它
发表论文 点击下载
1.Zhang, H., Sun, L., Zhou, Y. and Huang, J. (2017). Oracle inequalities and selection consistency for weighted lasso in high-dimensional additive hazards model. Statistica Sinica, 27, 1903-1920.
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2.Zhang, H., Wang, D. and Sun, L. (2017). Regularized estimation in GINAR(p) process. Journal of the Korean Statistical Society, In press.
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3.Zhou, J., Zhang, H., Sun, L. and Sun, J. (2017). Joint analysis of panel count data with informative observation process and a dependent terminal event. Lifetime Data Analysis, In press.
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4.Fang, S., Zhang, H., Sun, L. and Wang, D. (2017). Analysis of panel count data with time-dependent covariates and informative observation process. Acta Mathematicae Applicatae Sinica(English Series), 33, 147-156.
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5.Yoon, G., Zheng, Y., Zhang, Z., Zhang, H., Gao, T., Joyce, B., Zhang, W., Guan, W., Baccarelli, A., Jiang, W., Schwartz, J., Vokonas, P., Hou, L. and Liu, L.(2017). Ultra-high dimensional variable selection with application to normative aging study: DNA methylation and metabolic syndrome. BMC Bioinformatics, 18:156.

6.Zhang, H., Zheng, Y., Yoon, G., Zhang, Z., Gao, T., Joyce, B., Zhang, W., Schwartz, J., Vokonas, P., Colicino, E., Baccarelli, A., Hou, L. and Liu, L. (2017). Regularized estimation in sparse highdimensional multivariate regression, with application to a DNA methylation study. Statistical Applications in Genetics and Molecular Biology, 16, 159 - 171.

7.Wang, X, Wang, D. and Zhang, H. (2017). Poisson autoregressive process modeling via the penalized conditional maximum likelihood procedure. Statistical Papers. In press.

8.Zhang, H., Zheng, Y., Zhang, Z., Gao, T., Joyce, B., Yoon, G., Zhang, W., Schwartz, J., Just, A., Colicino, E., Vokonas, P., Zhao, L., Lv, J., Baccarelli, A.,Hou, L. and Liu, L. (2016). Estimating and testing high-dimensional mediation effects in epigenetic studies. Bioinformatics, 32, 3150–3154

9.Fang, S., Zhang, H. and Sun, L. (2016). Joint analysis of longitudinal data with additive mixed effect model for informative observation times. Journal of Statistical Planning and Inference,169, 43-55.

10.Liu, Y., Wang, D., Zhang, H. and Shi, N. (2016). Bivariate zero truncated Poisson INAR(1) process. Journal of the Korean Statistical Society.45, 260-275

11.Li, C., Wang, D. and Zhang, H. (2015). First-order mixed integer-valued autoregressive processes with zero-inflated generalized power series innovations. Journal of the Korean Statistical Society, 44, 232-246.

12.Zhang, H. and Wang, D. (2015). Inference for random coefficient INAR(1) process based on frequency domain analysis, Communications in Statistics: Simulation and Computation, 44, 1078-1100.

13.Jia, B., Wang, D. and Zhang, H.(2014). A study for missing values in PINAR(1) processes. Communications in Statistics: Theory and Methods, 43, 4780-4789.

14.Zhang, H., Wang, D. and Zhu, F. (2012). Generalized RCINAR(1) process with signed thinning operator. Communications in Statistics: Theory and Methods,41, 1750-1770.

15.Zhang, H., Zhao, H., Sun, J., Wang, D. and Kim, K. (2013). Regression analysis of multivariate panel count data with an informative observation process. Journal of Multivariate Analysis, 119, 71-80.

16.Zhang, H., Sun, J. and Wang, D. (2013). Variable selection and estimation for multivariate panel count data via the seamless-L0 penalty. The Canadian Journal of Statistics, 41, 368-385.

17.Zhang, H., Wang, D. and Zhu, F. (2011). Empirical likelihood inference for random coefficient INAR(p) process. Journal of Time Series Analysis, 32, 195-203.

18.Zhang, H., Wang, D. and Zhu, F. (2011). The empirical likelihood for first-order random coefficient integer-valued autoregressive processes. Communications in Statistics: Theory and Methods, 40, 492-509.

19.Wang, D. and Zhang, H. (2011). Generalized RCINAR(p) process with signed thinning operator. Communications in Statistics: Simulation and Computation, 40, 13-44.

20.Zhang, H., Wang, D. and Zhu, F. (2010). Inference for INAR(p) processes with signed generalized power serie thinning operator. Journal of Statistical Planning and Inference, 140, 667-683.