有人说他的教学生涯富有传奇色彩:早在1987年中师毕业后他就走上了讲坛,迄今已有38个年头了。从学前班的学生到博士生,他都教过; 从边远落后的少数民族聚居区到繁华的大都市的教学生活,他都亲身经历过。 在中国人民大学任教20年期间先后讲授了16门次研究生课程和4门本科生课程,其中包括新开的8门国际前沿统计学课程,内容涉及分层回归、分位回归、鞍点逼近、流行病学、金融风险管理、成份分析、高维复杂数据降维、统计诊断、小波分析、多元统计等当今统计学的热点话题,所选教材全部使用国际上一流院校普遍采用的优秀教材, 采用双语教学。 所带博士后、博士生及硕士研究生共计200多名。其主要工作经历如下:
1994. 02 — 1995.08 中国保险管理干部学院 助教
2001. 06 — 2004. 08 中国科学院数学与系统科学研究院系统所
2002. 08 — 2002. 11 香港中文大学统计系 助研
2002 01 — 2003. 12 加拿大国家数据库高等研究中心 博士后
2004. 01 — 2004. 07 加拿大卡尔加里数学与统计系 博士后
2004. 11 — 2005. 02 香港中文大学统计系 副研究员
2005. 07 — 2007. 02 香港中文大学统计系、香港浸会大学数学系 博士后
2007. 08 — 2007. 11 香港浸会大学数学系 访问学者
2008. 03 — 2008. 06 香港浸会大学数学系 访问学者
2008. 07 — 2009. 01 德国洪堡大学,SFB 649 Fellow 中方首席科学家
2008. 10 — 2009. 11 澳大利亚墨尔本大学, Research Fellow
2009. 12 — 2010. 01 德国洪堡大学,SFB 649 Fellow 中方首席科学家
2010. 10 — 2010. 11 德国洪堡大学,SFB 649 Fellow 中方首席科学家
2011. 07 — 2011. 07 香港中文大学统计系 访问学者
2011. 12 — 2012. 03 美国耶鲁大学医学院 高级访问教授
2012. 07 — 2012. 09 英国曼切斯特大学数学学院、布鲁奈尔大学数学系高级访问教授
2012. 11 — 2012. 12 日本东京大学数学信息系 访问教授
2012. 12 — 2013. 01 意大利佛罗伦萨大学经济学院 访问教授
2015. 09 — 2015. 10 Rhodes, 希腊
2015. 11 — 2015. 11 日本同志社大学
2017. 01 — 2017. 03 美国哥伦比亚大学
2004. 06 — 至今 中国人民大学 副教授、教授、博士生导师
1) 2024.01 — 至今, 首批中国人民大学“吴玉章特聘教授”
2) 2018.01 — 至今, 全国统计科学研究计划项目评审专家
3) 2017.09 — 至今, 中国现场统计研究会第十届理事会理事
4) 2017.09 — 至今, 北京市社科联专家
5) 2017.08 — 至今, 首批中国人民大学“杰出学者”青年学者
6) 2017.08 — 至今, 国际生物统计学会中国分会 (IBS-China) 常务理事
7) 2017.03 — 至今, 教育部学位与研究生教育发展中心通讯评审专家
8) 2016.03 — 至今, 北京高校少数民族代表人士
9) 2016.04 — 至今, 北京市哲学社会科学评奖专家
10) 2016.03 — 2019.02, 新疆维吾尔自治区“天山学者”
11) 2015.06 — 至今, 北京市科学技术委员会专家
12) 2015.11 — 至今, 国家社科基金同行评议专家
13) 2015.10 — 至今, 国家出版基金评审专家
14) 2015.10 — 至今, 国家社科中华学术外译专家
15) 2015.04 — 至今, 中国现场统计研究会高维数据统计分会常务理事
16) 2014.10 — 至今, 中国概率统计学会第十届理事会理事
17) 2014.04 — 至今, 中国博士后科学基金会评审专家
18) 2013.08 — 2017.07, 国际生物统计学会中国分会 (IBS-China) 常务理事
19) 2013.05 — 至今, 北京市自然科学基金评审专家
20) 2013.03 — 2015.02, 甘肃省“飞天学者”
21) 2013.02 — 至今 长江学者评审专家
22) 2012.02 — 至今, 国家留学基金评审专家
23) 2012.10 — 至今, 中国现场统计研究会生存分析分会秘书长
24) 2011.03 — 至今, 全国教育科学规划学科组专家
25) 2011.03 — 至今, 北京市哲学社会科学学科评审组成员
26) 2011.03 — 至今, 交通运输部规划研究院等重大项目评审、验收专家
27) 2011.02 — 至今, 教育部人文社科项目评审专家
28) 2010.08 — 至今, 美国统计协会会员 (ID. 165873)
29) 2010.01 — 2015.05, 北京市科学技术委员会专家
30) 2010.06 — 至今, 国际计量经济协会会员(ID. 1734779)
31) 2008.11 — 至今, 《统计学评论》(Statistics Review) 副主编
32) 2008.11 — 至今, 《统计研究》(Statistics Research) 编委
33) 2008.11 — 至今, 国家自然科学基金同行评议专家
34) 2008.07 — 2010.10, 德国洪堡大学,SFB 649 FELLOW, 中方首席科学家
35) 2006.01 — 2019.12, 教育部人文社会科学重点研究基地中国人民大学应用统计科学研究中心副主任
36) 2006.03 — 至今, 教育部“留学回国人员科研启动基金”评审专家
37) 2007.09 — 至今, 中国人民大学概率论与数理统计研究所副所长
38) 2001.01 — 至今, 担任超过50 本国际国内杂志的审稿人
近二十年来, 本人一直与国内外一些著名统计学家保持学术上的紧密联系与实质性合作。空中飞行距离累计达上百万里路,迄今为止已与国内外14名导师合作过,他们分布于亚洲、欧洲、美洲以及大洋洲。 先后在国际国内的学术刊物上发表300多篇文章,著书18部(合著)。
项目情况: 国外、境外项目情况: 作为主要负责人参于过的国外境外科研项目有14个:香港中文大学3个,香港浸会大学6个,加拿大ALBERTA 大学1个,CALGARY大学1个,德国洪堡大学2个,澳大利亚MELBOURNE 大学1个。
国内项目情况: 主持的科研项目37项, 其中包括本人主持的在研项目:国家社科基金(No. 07BTJ002),教育部重点基金(No. 108120),国家自然科学基金(No.10871201), 教育部哲学社会科学研究重大课题攻关项目(No. 15JZD015 )等。
2006年以后获奖情况
1. 教育部新世纪优秀人才 (排名第一) (2006 年,主持)
2. 第八届全国统计科学研究优秀成果奖 (二等奖, 排名第一)(2006 年,主持) (2006A2-03) 2008年
3. 第九届全国统计科学研究优秀成果奖(二等奖, 排名第一) (2008 年,主持)(2008B2-16) 2010年
4. 第十届全国统计科学研究优秀成果奖课题论文奖 (一等奖,排名第一)(2010年,主持)(2010A1-6)
5. 第十届全国统计科学研究优秀成果奖—统计教学奖(三等奖, 排名第一) (2010 年,主持);(2010E3-7)
6. 北京市第十届优秀统计科研成果优秀论文奖(2010 年,主持);
7. “Longitudinal study of Japanese youth: an analysis of mathematics and science achievements approach” 获2010年度亚洲地区日本研究资助计划财政奖(日本),http://www.sumitomo.or.jp/e/Jare/10jarelist.htm,主持 2012年
8. 第十一届全国统计科学研究优秀成果奖课题论文奖 (三等奖,排名第一)(2012年,主持)(2012A3-8)
9. 第十一届全国统计科学研究优秀成果奖—统计教学奖(三等奖, 排名第一) (2012 年,主持);(2012E3-9)
10. 北京市第十一届优秀统计科研成果优秀论文奖(2012 年,主持);
11. 中国人民大学十大教学优秀奖(2012年) 2014年
12. 北京市第十三届哲学社会科学优秀成果奖二等奖 (2014 年,主持); http://www.bjskl.gov.cn/ggl/201410/t20141028_10869.html
13. 北京市第十二届统计科学研究优秀成果评比优秀课题论文一等奖(2014 年,主持);
14. 中国人民大学优秀博士学文论指导老师(2014年)
15. 荣获北京市教育工会荣誉奖,为党的教育事业辛勤工作30年荣誉证书，2017年
16. 甘肃省优秀学位论文指导老师（证书编号：YS2019072), 2019年
17. 武汉市第十六次社会科学优秀成果二等奖，社科证字（2019）第053号
18. 中国公路学会科学技术奖，“交通运输经济运行分析理论与实践研究”，一等奖，（证书号：B20-1-005-008), 2020年
19. 中国交通运输协会科技进步奖,“交通运输指数理论与实践研究”，一等奖，批准奖励编号0287, 证书编 号：CT-A-2021013。获奖证明编号：CT-A-2021013-R06, 2021年
20. 交通运输重大科技创新成果入库证书（交通运输经济运行分析理论与实践研究），2021年12月
21. 首届中国统计学会，统计科学进步奖获奖证书，获奖项目：分层分位回归模型理论方法及应用, 证书号：0121306-2.
22. 中国人民大学优秀科研成果奖，成果名称：《现代非参数统计中的窗宽选择及应用》，科学出版社， 2019年，奖项类别：著作类；科研成果奖（2021）第03号。
23. 甘肃省优秀学位论文指导老师, 2022年
24. 宝钢教育奖优秀教师奖，2023年
(一) 主讲过的部分研究生、博士生课程(双语) Postgraduate courses (Renmin University of China)
《统计模型》Statistical Models (3 hours) 《分位回归》Quantile Regression (2 hours)
《分层模型》Hierarchical Models (3 hours)
《现代统计理论方法》Modern Statistical Theory and Methods (2 hours)
《鞍点逼近》Saddlepoint Approximations (2 hours)
《流行病风险统计估计》Statistical Estimation of Epidemiological Risk (2 hours)
《复杂数据统计分析》Statistical Analysis with Complex Data (2 hours)
《统计前沿》Frontiers in Statistics (2 hours)
《计算机密集型计算》Computer Intensive Methods (2 hours)
《量化风险管理》Quantitative Risk Management (3 hours)
《高等统计》Advanced Statistics (3 hours)
《统计学基础》The Fundamental Advanced Statistics for Phd Students (3 hours)
《高维数据分析》High Dimensional Data Analysis (2 hours)
《统计建模》Statistical Modeling (3 hours)
(二)主讲过的部分本科生课程(双语) Undergraduate course (The Renmin University of China)
《统计计算》Statistical Computation (2 hours)
《回归分析》Regression Analysis (3 hours)
《统计诊断》Statistical Diagnostics (3 hours)
《数理统计》Mathematical Statistics (3 hours)
《多元统计分析》Multivariate Statistical Analysis (3 hours)
该同志从教37余载,教过的学生人数过万, 其中最近15年左右指导的博士生、研究生多达200余人。
分位回归; 分层模型; 分层分位回归建模; 适应性平滑; 数据建模; 贝叶斯统计推断; 计算机密集计算; 极值和重尾分布; 函数型数据分析; 金融、经济计量与风险管理; 高阶降维; 统计中的逆问题; 大样本理论; 大范围数据分析; 模型选择; 非参数半参数建模; 顺序统计量; 量化金融; 稳健统计量; 鞍点逼近及应用; 时空建模; 统计诊断; 流行病风险中的统计方法; 随机模拟; 时间序列建模; 波动率模型;......
Books
1) Wu, X. Z. and Tian, M. Z. (2003), Diagnostics for Modern Regression Models. China Statistical Press. (In Chinese)
2) Tian, M. Z. (2011), Discovery and Innovation. Page 48–50, China Statistical Press. (In Chinese)
3) Gao, M. and Tian, M. Z., et al. (2013). Selected Empirical Analysis for Teaching in The Major of Statistics. Page 166–224, Chapter 7, (In Chinese)
4) Tian, M. Z. (2014). Theory, Methodology and Applications for Complex Data Statistical Inference, Science Press. (In Chinese)
5) Tian, M. Z. (2015). Advanced Theory for Hierarchical Quantile Modeling, Science Press. (In Chinese)
6) Tian, M. Z. (2015). Quantile Regression & Complex Hierarchical Data Analysis，China Intellectual Property Publishing House.
7) Tian, M. Z. (2015). Model Hierarchical Quantile Regression–Theory, Methodology and Applications, Tsinghua University Press. (In Chinese)
8) Tian, M. Z. (2017), Multivariate Statistical Analysis with R, China Renmin University Press.
9) Tian, M. Z. (2019). Bandwidth Selection and Its Applications in Modern Nonparametric Statistics, China Science Press. (In Chinese)
10) Tian, M. Z. (2022), Hierarchical Quantile Modeling Theory, Methodology and Applications, Science Press. (In English).
11) Tian, M. Z. (2023), Theory and Methodology of Monitoring and Prediction of Economic Situation Based on Big Data, Tsinghua University Press.
12) Tian, M. Z. (2024), Modern Multivariate Statistical Analysis, Science Press, Higher Education Press.
13) Tian, M. Z. and Tai, L. N. (2024), Fundamentals of Statistics and Data Analysis. The Open University of China Publishing & Media Group.
14) Tian, M. Z. (2024), Advanced Multivariate Statistical Analysis, Science Press, (to appear).
15) Tian, M. Z. (2024), Advanced Statistical Models, Science Press, in press.
16) Tian, M. Z. (2024), Theory, Methodologys of Censored Missing Quantile Regression and Its Applications, Science Press, in press.
17) Tian, M. Z. (2024), Advanced Statistical Modeling in Medicine, Elsevier, under review.
.........
1. Tian, M. Z. and Yu, K. M. (2024). Maozai Tian and Keming Yu's contributions to the Discussion of “Safe Testing” by Peter Grüunwald, Rianne de Heide, and Wouter Koolen. Journal of the Royal Statistical Society, Series B: Statistical Methodology, Manuscript ID JRSSB-Feb-2024-0122, to appear, (IF, 5.9, SCI, Q1).
2. Ma, S. P. and Tian, M. Z. (2024). A Censored Quantile Transformation Model for Alzheimer's Disease Data with Multiple Functional Covariate. Journal of the Royal Statistical Society: Series A: Statistics in Society, Manuscript ID JRSSA-Dec-2022-0269, to appear, (SCI, Q1).
3. Tian, Y. Z., Tang, M. L., Wong, C. and Tian, M. Z. (2024). Bayesian Analysis of Joint Quantile Regression for Multi-response Longitudinal Data with Application to Primary Biliary Cirrhosis Sequential Cohort Study. Statistical Methods in Medical Research, ? (1), 1–22, accept, DOI: 10.1177/09622802241247725. (SCI, Q1).
4. Xiong, W., Härdle, W. K., Wang, J. R., Yu, K. and Tian, M. Z. (2023). Mode-based Classifier: A Robust and Flexible Discriminant Analysis for High-dimensional Data. Statistical Sinica, SS-2023-0014, DOI: 10.5705/ss.202023.0014, accept, (SCI, Q2).
5. Guo, J. X., Pan, J. X., Yu, K. M., Tang, M. L. and Tian, M. Z. (2023). Quantile Regression and Smoothed Empirical Likelihood for Non-Ignorable Missing Data Based on Semi-Parametric Response Models. Science China Mathematics, SCM-2023-0633, to appear, https://doi.org/10.1007/s11425-023-2280-1 (SCI)
6. Xiong, W., Pan, H., Yu, K. M. and Tian, M. Z. (2024). A Weighted Quantile Regression Approach for Complex High-dimensional Heterogeneous Data. Science China Mathematics, 54 (2): 181–210. DOI: 10.1360/SSM-2022-0080 , (CSCD, Q1).
7. Nie, Y. W., Yang, Z., Lu, Y. Q., Bahani, M., Zheng, Y. L., Tian, M. Z., Zhang, L. P. (2024).Interaction between Air Pollutants and Meteorological Factors on Pulmonary Tuberculosis in Northwest China: A Case Study of Eight Districts in Urumqi, International Journal of Biometeorology, DOI：https://doi.org/10.1007/s00484-023-02615-z， (IF 3.6, SCI, Q2).
8. Zhang, L. P., Kurbanyaz, G, Tian, M. Z. (2024). Confidence Interval Construction of Risk Difference in Paired Design. Applied Mathematics-A Journal of Chinese Universities. 39 (1): 28–40.
9. Yu, Z. and Tian, M. Z. (2024). First Passage Density of Brownian Motion with Two-sided Piecewise Linear Boundaries. the Acta Mathematica Sinica, English Series, 1-16 [2024-01-B04]. http://kns.cnki.net/kcms/detail/11.2039.O1.20230509.0843.002.html. (SCI).
10. Bai, Y. X. and Tian, M. Z. (2024). Screening and Selection for Ultra-high Dimensional Quantile Regression with Missing Data and Measurement Error. Journal of Applied Statistics and Management, No. 21-0308 –, (CSSCI, CSCD).
11. Yang, L. P., Xie, N., Yao, Y. R., Wang, C. X., Rifhat, R., Tian, M. Z. and Wang, K. (2024). Hepatitis B Time Series in Xinjiang, China (2006-2021): Change Point Detection Based on the Mann-Kendall-Sneyers Test. Mathematical Biosciences and Engineering，21(2): 2458–2469, doi: 10.3934/mbe.2024108 , (SCI, Q2, IF: 2.6).
12. Liang, J. W. and Tian, M. Z. (2024). Imputed Quantile Vector Autoregressive Model for Multivariate Spatial-temporal Data. Statistical Analysis and Data Mining, https://doi.org/10.1002/sam.11658, (SCI).
13. Wang, W. X., Yin, X. J., Zhang, J. J. and Tian, M. Z. (2024). Variational Inference of Bayesian Quantile Regression in Linear Mixed Effect Model, Journal of Systems Science and Mathematical Sciences, 44 (1), 269–284, (CSCD).
14. Liang, Y. Y., Cao, S. Z., Zhou, M. Y. and Tian, M. Z. (2022). Regional division of air quality governance based on pseudo-quantile clustering with the view of functional data. Journal of Applied Statistics and Management,, No. 21–0062, to appear, (CSSCI, CSCD).
15. Kurbanyaz, G. and Tian, M.Z. (2023). Confidence Intervals Construction for Relative Difference under Binomial Sampling based on MOVER Method. Journal of Systems Science and Mathematical Sciences No. ….4, …., accept, (CSCD).
16. Tian, Y. Z., Wu, C. H., Tang, M. L. and Tian, M. Z. (2023). Bayesian Relative Composite Quantile Regression with Ordinal Longitudinal Data and Some Case Studies, Journal Of Statistical Computation and Simulation. GSCS-2023-0347.R2., accept, (SCI).
17. Li, Y., Chen, H. L. ang Tian, M. Z. (2024). Statistical measurement and spatiotemporal evolution characteristics of the development level of new quality productive forces. Statistics and Decision, No. 2024.02.03.0007, accept, (CSSCI).
18. Tian, Y. Z., Wu, C. H., Tai, L. N., Mian, Z. and Tian, M. Z. (2024). Bayesian Relative Composite Quantile Regression Approach of Ordinal Latent Regression Model with L1/2 Regularization, Statistical Analysis and Data Mining. https://doi.org/10.1080/00949655.2024.2335399，(SCI).
19. Zhao, X. Y., Rong, Y. H., Lin, J. Z.,Tian, M. Z. and Liang, J. W.（2024） Double Sparsity Garrotized Kernel Machine in High-dimensional Semiparametric Partially Linear Model. Communications in Statistics Simulation and Computation, https://doi.org/10.1080/03610918.2024.2329244, (SCI).
20. Niu, X. Y., Tian, Y. Z.,Tang, M. L. and Tian, M. Z. (2023). Multivariate Contaminated Normal Mixture Regression Modeling of Longitudinal Data Based on Joint Mean-Covariance Model, Statistical Analysis and Data Mining. 17 (1), e11653, https://doi.org/10.1002/sam.11653, (SCI).
21. Li, E. Q., Xiong, W., Pan, H. and Tian, M. Z. (2024). Variable Screening and Selection for Ultra-High Dimensional Competing Risks Data. Biometrical Journal, No. bimj.202300254.R2, (SCI).
22. Si, S., Gu, J.W. andTian, M. Z. (2004). Leveraging Single-case Results to Bayesian Hierarchical Modelling. Computational Statistics (2024). https://doi.org/10.1007/s00180-024-01516-y, (SCI).
23. Xiong, W., Pan, H., Wang, J. R. and Tian, M. Z. (2023). An Efficient Model-free Approach to Interaction Screening for High Dimensional Data, Statistics in Medicine, 42 (10), 1583–1605, https://doi.org/10.1002/sim.9688 ，(SCI)
24. Liang, J. W., Härdle, W. K. and Tian, M. Z. (2023). Imputed Quantile Tensor Regression for Near-sited Spatial-temporal Data. Computational Statistics and Data Analysis, 182, 107713, https://doi.org/10.1016/j.csda.2023.107713 , (SCI).
25. Zheng, Y. L., Emam, M., Lu, D. M., Tian, M. Z., Wang, K., Peng, X. W. (2023). Analysis of the effect of temperature on tuberculosis incidence by distributed lag non-linear model in Kashgar city, China. Environmental Science and Pollution Research, (IF 5.190, SCI, Q1). https://10.1007/s11356-022-22849-5 . 30:11530–11541
26. Zeng, T., Lu, Y. Q., Zhao, Y. J., Guo, Z. H., Sun, S. Z., Teng, Z. D., Tian, M. Z., Wang, J., Li, S. L., Fan, X. C., Wang, W. M., Cai, Y. L, Liao, G. Z., Liang, X., He, D. H., Wang, K. and Zhao, S., (2023). Effectiveness of the booster dose of inactivated COVID-19 vaccine against Omicron BA.5 infection: A matched cohort study of adult close contacts. Respiratory Research. (SCI). (IF:7.162/Q1).
27. Li, E. Q., Pan, J. X., Tang, M. L., Yu, K. M., Härdle, W. K., Dai, X. W. and Tian, M. Z. (2023). Weighted Competing Risks Quantile Regression Models and Variable Selection. Mathematics, 11, 1295. https://doi.org/10.3390/math11061295 . (SCI, Q1)
28. Wang, K., Luan, Z. M., Guo, Z. H., Lei, H., Zeng, T., Yu, L., Li, H. J. J., Tian, M. Z., Ran, J. J., and Zhao, S. (2023). Superspreading potentials of SARS-CoV-2 Delta variants across different contact settings in eastern China: a retrospective observational study. Journal of Infection and Public Health, 16 (5), 689–696. https://doi.org/10.1016/j.jiph.2023.02.024, (SCI). (IF:7.537/Q1).
29. Bai, Y. X. and Tian, M. Z. (2023). Variable Screening and Selection for Ultra-high Dimensional Additive Quantile Regression with Missing Data. Acta Mathematica Sinica, 1-25 [2024-01-04]. http://kns.cnki.net/kcms/detail/11.2038.o1.20230118.1438.008.html, (SCI).
30. Tao, L., Tai, L. N. and Tian, M. Z. (2023). Quantile Regression for Static Panel Data Models with Time-Invariant Regressors. Plos One, https://doi.org/10.1371/journal.pone.0289474, (SCI, SSCI, Q1).
31. Meng, L. J., Dai, X. W., Kurbanyaz, G, Chen, X. K. and Tian, M. Z. (2023). Profile Likelihood Estimation of Spatial Variable Coefficient Stratified Autocorrelation Model and Its Application. Acta Mathematicae Applicatae Sinica, ?4 (2), 1–24, accept, (CSCD).
32. Bai, Y. X., Qian, M. L. and Tian, M. Z. (2023). Variable Selection of Partial Linear Additive Quantile Regression under Complex Data. Statistics and Decision, No. 2022.10.12.0005, accept, (CSSCI).
33. Ma, S. P., Yu, K. M., Tang, M. L., Pan, J. X., Härdle, W. K and Tian, M. Z. (2023). A Bayesian Multi-stage Spatio-temporally Dependent Model for Spatial Clustering and Variable Selection, Statistics in Medicine, 42 (26): 4794–4823, (SCI)., http://dx.doi.org/10.1002/sim.9889, accept, (SCI, IF:2.497/Q1).
34. Liu, Y. X., Wang, Z. H. and Tian, M. Z. (2023). Composite Quantile Regression Estimation for Varying Coefficient Partially Functional Linear Models. Journal of Applied Statistics and Management, DOI:10.13860/j.cnki.sltj.20230629-001, (CSSCI, CSCD).
35. Liang, J. W. and Tian, M. Z. (2023). Imputed Mean Tensor Regression for Near-sited Spatial temporal Data. Journal of Applied Statistics, https://doi.org/10.1080/02664763.2023.2176470, (SCI, SSCI).
36. Liang, Y. Y. and Tian, M. Z. (2023). Estimation of Generalized Functional Partial Spatial Varying Coefficient Models and Its Application. Acta Mathematicae Applicatae Sinica, 46 (5) 813–834, (CSCD).
37. Zhou, X. and Tian, M.Z. (2023). Parameter Inference of Gamma Distribution with Left Truncated and Right Censored Data, Journal of Shandong University of Technology (Natural Science Edition), … , (1)，…– to appear.
38. Zhang, L. P. and Tian, M. Z. (2023). Parameter Inference of Inverse Weibull Distribution under Generalized Progressive Hybrid Censoring Scheme, Journal of Systems Science and Mathematical Sciences, ?1(?3):?8 – 8?, (CSSCI, CSCD).
39. Xiong, W., Wang, J., Pan, H. and Tian, M.Z. (2023). Research on Multiple Robust Imputation for High-dimensional Missing Data. Journal of Statistical and Information, 38 (2):3 –15 , (CSSCI).
40. Kurbanyaz, G, Meng, L. J. and Tian, M.Z. (2022). Orthogonality-projection-based Estimation for Mixed Geographically Weighted Regression Models with Heteroscedastic Errors. Statistics and Decision, No. 221114334, accept, (CSSCI).
41. Dai, X., Huang, S., Jin, L., Tian, M., and Shi, L. (2023). Wild Bootstrap-based Bias Correction for Spatial Quantile Panel Data Models with Varying Coefficients. Mathematics, No. mathematics-2309209. https://doi.org/
42. Xiong, W., Yang, H. X. and Tian, M. Z. (2021). Research on Live Stream Economy via Weibo Social Network. Journal of Applied Statistics and Management, No. 22-0101–, to appear, (CSSCI, CSCD).
43. Gu, Y. T., Tian, M. Z., Zhang, G. and Chu, C. (2023). Effect of Paired Assistance Program on the Income Level of Urban and Rural Residents in Xinjiang —Analysis at the Provincial and Municipal Level. Journal of Statistics. 4 (3), 33–56.
44. Li, E. Q., Tang, M. L., Tian, M. Z. and Yu, K. M. (2023). Optimal subsampling proportional subdistribution hazards regression with rare events in big data, Statistics and Its Interface. (No. SII2212-023), under revision. (SCI)
45. Tao, L., Tai, L. N., Qian, M. L. and Tian, M. Z. (2023). A New Instrumental-Type Estimator for Quantile Regression Models. Mathematics, No.2492776, accepted, (SCI, Q1).
46. Guo, J. X. and Tian, M. Z. (2023). Semiparametric Nonignorable Nonresponse Model And Smoothed Quantile Regression Based on Sufficient Dimension Reduction. Journal of Systems Science and Mathematical Sciences, No. 22842:14-?, accept, (CSCD).
47. Lu Y, Guo Z, Zeng T, Sun S, Lu Y, Teng Z, Tian M, Wang J, Li S, Fan X, Luan Z, Wang W, Cai Y, Wang K, Zhao S. (2023). Case clustering, contact stratification, and transmission heterogeneity of SARS-CoV-2 Omicron BA.5 variants in Urumqi, China: An observational study. Journal of Global Health. doi:10.7189/jogh.13.06018 (SCI, SSCI, Q1, IF = 7.2).
48. Meng, L. J., Kurbanyaz, G., Wang, Z. H. and Tian, M. Z. (2023). Bayesian-INLA Estimation of Varying Coefficient Spatial Autocorrelation Model. Journal of Systems Science and Mathematical Sciences, ?1(?3):?8 – 8?, to appear, (CSSCI, CSCD).
49. Zhang, J. J. Wang, W. X. and Tian, M. Z. (2022). Variational Bayesian of quantile regression in high dimensional mixed effect model, Statistics and Decision, No. 202307040014, accept, (CSCD).
50. Zeng, T., Wang, K. L., Guo, Z. H., Sun, S. Z., Zhai, Z. Y., Lu, Y. Q., Teng, Z. D., He, D. H., Wang, K., Tian, M. Z., and Zhao, S. (2023). Distinguishing the Vaccine Effectiveness of Inactivated BBIBP-CorV Vaccine Booster Against the Susceptibility, Infectiousness, and Transmission of Omicron Stains: A Retrospective Cohort Study in Urumqi, China. Infectious Diseases and Therapy, 12, 2405–2416. https://link.springer.com/article/10.1007/s40121-023-00873-3, (SCI, Q2, IF = 5.1).
51. Zhou, M. Y. and Tian, M. Z. (2023). Parameter Estimation Based on Guass-Seidel Type Iterative Hierarchical Linear Model. Journal of Applied Statistics and Management, No., accept, (CSCD).
52. Hu, Y. N., Yin, W. X. and Tian, M. Z. (2023). How Does the Minimum Wage Affect the Manufacturing Labor Cost? —Analysis Based on the Panel Data Quantile Treatment Effect Model. Journal of Applied Statistics and Management, 42 (6), 951–963, (CSSCI, CSCD).
53. Yang, L. P., Xie, N., Yao, Y. R., Wang, C. X., Rifhat, R., Tian, M. Z. and Wang, K. (2023). Multiple Change Point Analysis of Hepatitis B Reports in Xinjiang, China from 2006 to 2021. Frontiers in Public Health, Infectious Diseases: Epidemiology and Prevention, DOI: 10.3389/fpubh.2023.1223176, (SCI, SSCI, Q1, IF: 6.461).
54. Liang, J. W. and Tian, M. Z. (2023). Nonparametric Maximin Aggregation for Data with Inhomogeneity. Communications in Statistics - Theory and Methods, DOI:10.1080/03610926.2023.2279913, accept, (SCI).
55. Xiong, W., Tang, M. L. and Tian, M. Z. (2023). Robust and Sparse Learning of Varying Coefficient Models with High-dimensional features. Journal of Applied statistics, 50 (16), 3312–3336, https://doi.org/10.1080/02664763.2022.2109129 , (SCI, SSCI).
56. Liang, Y. Y., Tian, Y. and Tian, M. Z. (2023). Estimation of Bivariate Penalty Spline Quantile Regression for Spatial Varying Coefficient Model. Journal of Applied Statistics and Management, 42 (5), 838–855 (CSSCI).
57. Liu, S. and Tian, M. Z. (2023). Mutual Information Maximization for Semi-supervised Anomaly Detection, Knowledge-Based Systems, https://doi.org/10.1016/j.knosys.2023.111196, 1–13, (SCI, Q1, IF: 8.8).
58. Guo, J. X., Liu, F. G., Härdle, W. K, Zhang, X. L, Wang, K., Zeng, T., Yang, L. P. and Tian, M. Z. (2023). Sampling Importance Resampling Algorithm with Nonignorable Missing Response Variable Based on Smoothed Quantile Regression. Mathematics, 2023, 11 (24), https://doi.org/10.3390/math11244906, (SCI, Q1, IF:2.4)
59. Cheng, Y. and Tian, M. Z. (2023). Parameter inference based on Marshall-Olkin Alpha Power Gumbel type-II distribution. Journal of Henan Institute of Science and Technology（Natural Science Edition), 51 (6), 39–47, (RCCSE).
60. Cheng, Y. and Tian, M. Z. (2023). Parameter Estimation and Application based on the New Extended Weibull distribution. Journal of Shandong University of Technology (Natural Science Edition), ? (6), ?–47, ().
61. Wang, C. Y. and Tian, M. Z. (2023). The Large Sample Property of the Iterative Generalized Least Squares Estimation for Hierarchical Mixed Effects Model. Frontiers of Mathematics in China, 18 (5): 327-339. https://doi.org/10.3868/s140-DDD-023-0023-x
62. Tian, Y. Z. and Tian, M. Z., Chen, P. (2023). Parameters Estimation and Application of Generalized Exponential Distribution under Grouped and Right-censored Data. Frontiers of Mathematics in China, 18 (3): 165-174. https://doi.org/10.3868/s140-DDD-023-0013-x.
63. Zhang, L. P. and Tian, M. Z. (2023). Parameter inference of inverse Weibull distribution under Progressively Type-II Censored Data, Journal of Shandong University of Technology (Natural Science Edition), 37(03): 39–45，DOI: 10.13367/j.cnki.sdgc.2023.03.002, (CSCD).
64. Yu, Z., Yu, K. M., Härdle, W. K, Zhang, X. L., Wang, K. and Tian, M. Z. (2022). Bayesian Spatio-temporal Modeling for Inpatient Hospital Costs of Alcohol-related Disorder, Journal of the Royal Statistical Society, 185 (2), 644–667, https://doi.org/10.1111/rssa.12963 , (SCI, SSCI, Q1).
65. Ma, S. P. and Tian, M. Z. (2022). Heteroscedasticity Testing for Semi-parametric Multi-index Models Based on Partial Dimension Reduction Method. Science in China Series A: Mathematics, 52 (8), 935– 968, https://doi.org/10.1360/SSM-2019-0288 , (CSCD, Q1).
66. Zhu, X., Song, Z., Sen, G., Tian, M. Z., Zheng, Y. L., and Zhu, B. (2023). Prediction Study of Electric Energy Production in Important Power Production Base, China. Scientific Reports, 12 (1), 21472. https://doi.org/10.1038/s41598-022-25885-w. (IF 4.99, SCI, Q1).
67. Liang, J. W., Zhang, X. L., Wang, K., Tang, M. L. and Tian, M. Z. (2022). Discovering Dynamic Models of COVID-19 Transmission. Transboundary and Emerging Diseases, https://doi.org/10.1111/tbed.14263, (SCI, Q1).
68. Yang, H. X., Xiong, W., Zhang, X. L., Wang, K. and Tian, M. Z. (2022). Penalized Homophily Latent Space Models for Directed Scale-free Networks. Plos One, 16(8): e0253873. https://doi.org/10.1371/journal.pone.0253873, (SCI, SSCI, Q1).
69. Zhou, P., Yu, Z., Tian, M. Z. and Ma, J. Y. (2022). Communication-Efficient Distributed Estimation for Generalized Linear Models with a Diverging Number of Covariates. Computational Statistics and Data Analysis, 157 ,107154, https://doi.org/10.1016/j.csda.2020.107154, (SCI).
70. Yang, Z., Wang, C. C., Nie, Y.W., Sun, Y. H., Tian, M. Z., Ma, Y. H., Zhang, Y. X., Yuan, Y. M. and Zhang, L. P. (2022). Investigation on spatial variability and influencing factors of drinking water iodine in Xinjiang, China. Plos One, DOI: 10.1371/journal.pone.0261015 (SCI, SSCI, Q1).
71. Zhang, Y. X., Wang, Q. and Tian, M. Z. (2022). Smoothed Quantile Regression with Factor-augmented Regularized Selection Model. Mathematics- Mathematics and Computer Science, 10, 2935, 1–30, https://doi.org/10.3390/math10162935, (SCI, Q1).
72. Wang, C. Y., Tian, M. Z. and Tang, M. L. (2022). Nonparametric Quantile Regression with Missing Data Using Local Estimating Equations. Journal of Nonparametric Statistics, 34 (1), (SCI).
73. Wang, K., Luan, Z. M., Guo, Z. H., Ran, J. J., Tian, M. Z. and Zhao, S. (2022). The Association Between Clinical Severity and Incubation Period of SARS-CoV-2 Delta Variants: Retrospective Observational Study. JMIR Public Health and Surveillance, vol. 8, iss. 11, e40751, (SCI, SSCI, IF:14.557/Q1).
74. Rui, R. X.,Tian, M. Z. and Xiong, W. (2022). Exploration of the Impact of Political Ideology Disparity for COVID-19 Transmission in the United States. BMC Public Health. https://doi.org/10.1186/s12889-022-14545-3, (SCI, IF:4.135/Q2)
75. Wang, Z. H., Bai, Y. X., Härdle, W. K, and Tian, M. Z. (2023). Smoothed Quantile Regression for Partially Functional Linear Models in High Dimensions. 65 (7), Biometrical Journal, http://dx.doi.org/10.1002/bimj.202200060 , (SCI, IF:1.715/Q2)
76. Liu, Y. X., Wang, Z. H., Tian, M. Z. and Yu, K. M. (2022). Estimation and variable selection for generalized functional partially varying coefficient hybrid models, No. STPA-D-22-00330R1, Statistical Papers, to appear, (SCI, IF:1.523/Q3)
77. Liang, J. W. and Tian, M. Z. (2023). Sparse Regression for Low Dimensional Time Dynamic Varying Coefficient Models with Application to Air Quality Data. Journal of Applied Statistics, 50 (6), 1378–1399, https://doi.org/10.1080/02664763.2022.2028131 , (SCI, SSCI).
78. Ma, S. P., Zhang, X. L., Wang K., Zhang, L. P., Wang, L., Zeng, T., Tang, M. L. and Tian, M. Z. (2022). Exploring the Risk Factors of COVID-19 Delta Variant in the USA Based on Bayesian Spatio-Temporal Analysis, Transboundary and Emerging Diseases, 1–14 , DOI: 10.1111/tbed.14623 , (SCI, Q1).
79. Nie, Y. W., Lu, Y. Q., Wang, C. C., Yang, Z., Sun, Y. H., Zhang, Y. X., Tian, M. Z., Rifhat, R. and Zhang, L. P. (2022). Effects and Interaction of Meteorological Factors on Pulmonary Tuberculosis in Urumqi, China, 2013–2019. Frontiers in Public Health, Vol. 10, https://doi.org/10.3389/fpubh.2022.951578, (SCI, SSCI, IF:6.461)
80. Luan, Z. M., Yu, Z. X., Zeng, T., Wang, R. and Tian, M. and Wang, K., (2022). A Study on the Factors Influencing the Transfer of COVID-19 Severe Illness Patients out of the ICU based on Generalized Linear Mixed Effect Model, Mathematical Biosciences and Engineering, 19 (10): 10602–10617, (SCI, IF: 2.194/Q3).
81. Yang, Z., Li, C., Wang, C. C., Nie, Y. W., Zhang, Y. X., Tian, M. Z., Zhang, L. P. (2022). Assessing the impact of meteorological conditions on outpatient visits for childhood respiratory diseases in Urumqi, China. Journal of Occupational and Environmental Medicine. 15, 921–931, (SCI).
82. Nie, Y. W., Wang, C. C., Yang, L., Yang, Z., Sun, Y. H., Tian, M. Z., Ma, Y. H., Zhang, Y. X., Yuan, Y. M. and Zhang, L. P. (2022). Relationship Analysis of Inorganic Arsenic Exposure and Metabolic Syndrome based on Propensity Score Matching in Xinjiang,China. Diabetes, Metabolic Syndrome and Obesity: Targets and Therapy. 15,921–931, (SCI).
83. Hu, Y. N., Wang, J. T. and Tian, M. Z. (2022). Estimation and Variable Selection for Semiparametric Spatial Quantile Regression Model. Journal of Applied Statistics and Management, 1-15, https://doi.org/10.13860/j.cnki.sltj.20210722-006 , accept, (CSSCI, CSCD).
84. Hou, J., Wang, Z. H., Tian, M. Z. and Dou, Y. (2022). Research on Influencing Factors of House Prices Based on Multi-Bandwidth GWTR Model. Journal of Applied Statistics and Management, 1-12, https://doi.org/10.13860/j.cnki.sltj.20210722-025 , (CSSCI, CSCD).
85. Hu, Y. N., Wang, J. T. and Tian, M. Z. (2022). High-dimensional Partially Linear Additive Spatial Quantile Regressive Model. Journal of Applied Statistics and Management, No.20-0D85, accept, (CSSCI, CSCD).
86. Zhang, Y. X. and Tian, M. Z. (2022). Joint Modeling of Count-Continuous Data and Its Application. Statistics & Decision, 38 (13), 46–51, (CSSCI).M
87. Kurbanyaz, G, and Tian, M.Z. (2022). Construction of Test Statistics for Odds Ratio Under Independent Inverse Sampling, Statistics and Decision, 38 (05), 5–10，(CSSCI).
88. Liang, Y. Y. and Tian, M. Z. (2022). Epidemic Modeling Based on Hierarchical Bayesian Spatio-temporal Poisson Model. Journal of Systems Science and Mathematical Sciences, 42 (2), 462–472, (CSCD).
89. Liang, Y. Y. and Tian, M. Z. (2022). Quantile Regression Estimation of Spatial Partial Linear Variable Coefficient Models. Statistics and Decision, 38 (09) 36–41, (CSSCI).
90. Zhang, L. P. and Tian, M. Z. (2022). Comprehensive Evaluation of Competitiveness Level of Catering Industry in Xinjiang Based on PCA-TOPSIS Method, Statistics and Management, accept. 37 (1)，102–108.
91. Zhou, X., and Tian, M.Z. (2022). Research on the Level of Regional Economic Development Based on Factor Analysis and Canonical Correlation Analysis -A Case Study of Xinjiang, Statistics and Management, 37 (1)，42–47.
92. Yu, Z., Ju, T. T., Wang, C. J. and Tian, M. Z., (2022). Hierarchical Shrinkage Models via Variational Bayes and Its Application. Journal of Applied Statistics and Management, No.21–0129, accept, (CSSCI, CSCD).
93. Kurbanyaz, G, Meng, L. J., and Tian, M.Z. (2022). Bayesian analysis of novel coronavirus pneumonia data in Urumqi, Applied Mathematics A Journal of Chinese Universities, 37(2): 226–236 (CSCD).
94. Zuo, Q., Luo, Y. X., Tian, M. Z. and Zhao, X. Y. (2022). Unconditional quantile regression for panel data with fixed effect and its application. Journal of Applied Statistics and Management, No. 190506, (CSSCI, CSCD).
95. Sun, Y. H., Tian, M. Z., Nie, Y. W., Yang, Z. and Zhang, L. P. (2022). Application of Spatial Panel Data Model in the Analysis of National Tuberculous Surveillance Data from 2015 to 2019. Chinese Preventive Medicine, 23(6) 436–441(CSCD).
96. Nie, Y. W., Ma, Y. H., Wang, C. C., Tian, M. Z., Yang, Z., Sun, Y. H., Zhang, Y. X., Rifhat, R. and Zhang, L. P. (2022). Analysis of HPV Infection Characteristics and Trend of Cohort Population in Karamay City, Xinjiang, 2010-2019 based on Joinpoint and APC Model. Modern Preventive Medicine, 49 (11), 1921 – 1925, (CSCD).
97. Kurbanyaz, G, and Tian, M.Z. (2022). Spatial Heteroscedasticity Test for Mixed Geographically Weighted Regression Models, Journal of Applied Statistics and Management, No. 21–0215, , (CSSCI, CSCD).
98. Haritebieke, S., Bahani, M., Nie, Y. W., Tian, M. Z., Zhang, L. P. (2022). Incidence trend and age-period-cohort analysis of pulmonary tuberculosis in China. Chinese Preventive Medicine:1-10.
99. Bai, Y. X., Tian, M. Z., Tang, M. L. and Lee, W. Y. (2021). Variable Selection for Ultra-high Dimensional Quantile Regression with Missing Data and Measurement Error. Statistical Methods in Medical Research, 30 (1), 129–150, (SCI, Q1).
100. Rui, R. X., Tian, M. Z., Tang, M. L., Ho, T. S. and Wu, C. H. (2021). Analysis of the Spread of COVID-19 in the USA with Spatio-Temporal Multivariate Time Series Model. International Journal of Environmental Research and Public Health, 18 (2), 774, (SCI, SSCI, Q2).
101. Tian, Y. Z. Tang, M. L. Chan, W. S. and Tian, M. Z. (2021). Bayesian Bridge-Randomized Penalized Quantile Regression for Ordinal Longitudinal Data, with Application to Firm's Bond Ratings. Computational Statistics, 36 (2), 1289–1319, (SCI).
102. Rui, R. X. and Tian, M. Z. (2021). Joint Estimation of Case Fatality Rate of COVID-19 and Power of Quarantine Strategy Performed in Wuhan, China. Biometrical Journal, 63 (1), 46–58, (SCI, Q3).
103. Ma, S. P., Sun, Q. H, Wu, Y. X. and Tian, M. Z. (2021). Research on Tensor Sufficient Dimension Reduction Method and Its Application. Statistical Research, 38 (02):114-134, (CSSCI).
104. Yan, M. B. and Tian, M. Z. (2021). Selection of High Dimensional Variables Based on Randomized Adaptive Lasso. Statistical Research, 38 (1): 147-160, (CSSCI).
105. Bai, Y. X. and Tian, M. Z. (2021). Variable Selection for Sparse Nonlinear Functional Model. Statistical Research, 38 (5):109 – 120. (CSSCI).
106. Wang, Z. H., Liu, Y. X., Tian, M. Z. and Chen, X. K. (2021). Functional Partially Varying Coefficient Models for Zero-Inflated Count Data. Statistical Research, 38 (7), 127 – 139,
(CSSCI).
107. Tian, Y. Z., Wang, L. Y. Tang, M. L., and Tian, M. Z. (2021), Weighted Composite Quantile Regression for Longitudinal Mixed Effects Models with Application to AIDS Studies. Communications in Statistics - Simulation and Computation, 50 (6), 1837–1853, (SCI, EI)
108. Dai, X. W., Li, E. Q. and Tian, M.Z. (2021). Quantile Regression for Varying Coefficient Spatial Error Models, Communications in Statistics – Theory and Methods, 50 (10), 2382–2397, (SCI, EI).
109. Liu, Y. X., Rui, R. X. and Tian, M. Z. (2021). A Novel Profile Composite Quantile Regression Estimation for the Partial Linear Variable-Coefficient Model. Acta Mathematicae Applicatae Sinica, 44 (2), 159–174, (CSCD).
110. Cao, R. and Tian, M. Z. (2021). Study on Executive Compensation of Private Listed Companies Based on Unconditional Quantile Regression, Systems Engineering-Theory & Practice, 41(1): 24–33, (EI, CSCD).
111. Kurbanyaz, G, Meng, L. J., and Tian, M.Z. (2021). Confidence Interval Construction for Conditional Odds Ratio in Matched-Pair Design, Journal of Systems Science and Mathematical Sciences, 41(03):824 – 836. (CSCD).
112. Zhang, Y. X., Meng, S. W., and Tian, M. Z. (2021). A Semi-parametric Bayesian Hierarchical Quantile Regression Model and Its Application in Analysis of Insurance Company Costs. Journal of Applied Statistics and Management, 40 (3):381 – 394, (CSSCI, CSCD).
113. Hou, J. and Tian, M. Z. (2021). Parameter Estimation of Mixed-GTWR Based on Variable Selection. Journal of Mathematics in Practice and Theory, 51(7), 110–118, (CSCD).
114. Liu, Y., An, B. W. and Tian, M. Z. (2021). Likelihood Test and Model Comparison of Zero-and-one-inflated Poisson Model. Statistics & Decision, 37 (13), 20–24, (CSSCI, CSCD).
115. Chu, Z. J., Tai, L. N., Xiong, W., Guo, X. and Tian, M. Z. (2021). The Horvitz-Thompson Weighting Method for Quantile Regression Estimation in the Presence of Missing Covariates. Journal of Mathematical Research with Applications, 41(3):303-322, (CSCD).
116. Zhou, M. Y. and Tian, M. Z. (2021). Statistical Inference of Hierarchical Linear Regression Model Based on Nested Structure. Statistics and Application, 10 (1), 173–182, (CSCD).
117. Tian, Y., Ma, S. P., Rui, R. X., Yu, Z. and Tian, M. Z. (2021). The Analysis of Impact of Brexit on the Post-Brexit EU Using Intervented Multivariate Time Series, Acta Mathematicae Applicatae Sinica (English Series), 37 (3), 441–458, (SCI).
118. Zhang, Y. X. and Tian, M. Z. (2021). Research and Application of Partial Linear Single Index Composite Quantile Regression Based on Bayesian. Journal of Systems Science andMathematical Sciences, 41(5):1381–1399., (CSSCI).
119. Liu, Y. and Tian, M. Z. (2021). Analysis of The Temporal and Spatial Differences of the Expenditure of Basic Pension Fund for Urban Workers–Based on GTWR Model and PanelQuantile Regression Model. Journal of Shanxi Normal University (Natural Science Edition), 35 (1):22–28., (CSCD).
120. Liu, Y. X., Wang, Z. H., Rui, R. X. and Tian, M. Z. (2021). Estimation for Generalized Functional Partially Varying Coefficient Hybrid Models. Journal of Systems Science and Mathematical Sciences, 41 (6), 1742-1760, (CSCD).
121. Rui, R. X., Liu, Y. X., Wang, Y. H. and Tian, M. Z. (2021). High-dimensional Conditional Mean Hypothesis Test and Its Application in the Diagnosis of Parkinson's Disease. Journal of Applied Statistics and Management, 40 (4), 571–584, (CSSCI, CSCD).
122. Cao, S. Z. and Tian, M. Z. (2021). Bayesian estimation of exponential distribution parameters based on uninformed priori under Stein loss function. Value Engineering, 33, 164 –168, (CSSCI).
123. Tian, Y. Z., Tang, M. L., and Tian, M. Z. (2021), Bayesian Joint Inference for Multivariate Quantile Regression Model With L_1/2 Penalty. Computational Statistics, 36(6), 2967–2994 , (SCI, EI).
124. Tian, Y. Z. and Tian, M. Z. (2021). Bayesian LASSO-Regularized Weighted Composite Quantile Regression with Its Application. Chinese Journal of Applied Probability andStatistics. Vol. 37 (4): 390–404.
125. Li, E. Q., Tian, M. Z. and Tang, M. L. (2020). Variable Selection in Competing Risks Models Based on Quantile Regression. Statistics in Medicine, 38 (23): 4670–4685, (SCI).
126. Qian, M. L., Tao, L., Li, E. Q. and Tian, M. Z. (2020). Hypothesis Testing for Identity of High-dimensional Covariance Matrices. Statistics and Probability Letters, 161,1–12, (SCI).
127. Bai, Y. X., Qian, M. L. and Tian, M. Z. (2020). Joint Mean-covariance Random Effect Model for Longitudinal Data. Biometrical Journal, 62, 7-23, (SCI).
128. Wu, Y. K., Hu, Y. N., Zhou, J. and Tian, M. Z. (2020). Simultaneous Estimation of Multiple Conditional Regression Quantiles, Acta Mathematicae Applicatae Sinica (English Series), 36 (2), 448–457, (SCI)
129. Tian, Y. Z., Wang, L. Y., Tang, M. L. and Tian, M. Z. (2020), Likelihood-based Quantile Mixed Effects Models for Longitudinal Data with Multiple Features via MCEM Algorithm, Communications in Statistics - Simulation and Computation, https://doi.org/10.1080/03610918.2018.1484477 , 49 (2), 317–334, (SCI, EI).
130. Xia, L. L. and Tian, M. Z. (2020). Penalty likelihood estimation for a class of constrained generalized additive model with zero-inflated count data. Statistics and Decision, 36 (2), 16 – 20, (CSSCI).
131. Dai, X. W., Yan, Z., Tian, M. Z. and Tang, M. L. (2020). Quantile Regression for General Spatial Panel Data Models with Fixed Effects. Journal of Applied Statistics, 47 (1), 45–60, (SCI, SSCI).
132. Dai, X. W., Jin, L. B., Tian, Y. Z., Tian, M. Z. and Tang, M. L. (2020). Quantile Regression for Panel Data Models with Fixed Effects under Random Censoring. Communications in Statistics-Theory and Methods, 49 (18), 4430–4445, (SCI, SSCI, EI).
133. Wu, Y. K., Tian, M. Z. and Tang, M. L. (2020). General Composite Quantile Regression: Theory and Methods. Communications in Statistics – Theory and Methods, 49 (9), 2217–2236, (SCI, EI).
134. Yang, L., Tao, L. and Tian, M. Z. (2020). Qunatile Regression Based on Multi-period DID Method and Its Applications. Statistics & Decision, 5, 25–28, (CSSCI).
135. Tai, L. N., Qian, M. L. and Tian, M. Z. (2020). Sample Selection Parametric Quantile Regression and Its Application in Distribution Decomposition of Wage, Statistical Research, 37(1), 62–73 (CSSCI).
136. Tai, L. N., Tao, L. and Tian, M. Z. (2020). Innovation Ideas of Government Statistics Work Based on Big Data Supply Chain. Statistics & Decision, 12, 156 –159, (CSSCI).
137. Liang, J. W. and Tian, M. Z. (2020). Outlier Diagnosis and Estimation via Volume Sampling in Big Data. Journal of Applied Statistics and Management, 39 (2), 223–235, (CSCD, CSSCI).
138. Tian, Y. Z., Wang, L. Y., Tang, M. L., Zang, Y. C. and Tian, M. Z. (2020), Likelihood-based Quantitle Autoregressive Distributed Lag Models and Its Applications. Journal of Applied Statistics, 47 (1), 117–131, (SCI, SSCI).
139. Liang, J. W. and Tian, M. Z. (2020). Sufficient Dimension Reduction Method based on Maximin Effect for Heterogeneous Data. Journal of Systems Science and Mathematical Sciences, 40 (5), 902–916, (CSCD).
140. Tao, L., Tai, L. N. and Tian, M. Z. (2020). Quantile Regression for Panel Data with Fixed Effects and Comparative Research. Statistics and Decision, 17, 9–13, (CSSCI).
141. Mu, J. and Tian, M. Z. (2020). Bayesian Hierarchical Regression Model with Multivariate Laplace Distribution and Its Application. Journal of Applied Statistics and Management, 39 (3) : 438–448, (CSSCI, CSCD).
142. Yan, M. B. and Tian, M. Z. (2020). Variable Significance Test after Selection under Various Distributions and Its Application to CEPS Data. Journal of Systems Science and Mathematical Science, 40 (1): 141 – 155, (CSCD).
143. Wang, Z. H., Tian, M. Z. and Hou, Z. M. (2020). Measuring Quantile Effects Based on Partial Least Squares Path Model, Journal of Systems Science and Mathematical Science, 40 (4): 738–750, (CSCD).
144. Bai, Y. X., Yan, M. B., Tian, M. Z. and Zhai, H. W. (2020). Evaluating the Quality of Multidimensional Statistical Data Based on the Bootstrap Method. Statistics & Decision, 11, 5–9, (CSSCI).
145. Zhang, C. L. and Tian, M. Z. (2020). Construction of Bootstrap Confidence Intervals Based on Bayes. Statistics and Decision, 1, 32-35, (CSSCI).
146. Luo, Y. X., Zhang, M. and Tian, M. Z. (2020). The Research and Application of Additive Quantile Regression Models for Panel Data. Statistical Research, , 37 (2), 105–118, (CSSCI).
147. Hou, Z. M., Tian, M. Z., Wang, Z. H. and Dou, Y. (2020). Study on The Impact of Technological Innovation on the Urbanization and Urban-rural Income Inequality—An Empirical Analysis Based on Western National Agglomeration Area. Journal of Mathematics in Practice and Theory, 50 (2)，53–64, (CSSCI, CSCD).
148. Guo, J. X., Xu, H., Zhu, W. Q. and Tian, M. Z. (2020). Distributed Estimation for Heterogeneous Big Data. Statistical Research, 37(10),104 – 114, (CSSCI).
149. Liu, Y. and Tian, M. Z. (2020). Pricing of "Take Photos and Make Money" APP Task Based on Logistic Regression Model, China Price, 8, 98 –101, (CSSCI)
150. Hu, Y. N., Wang, J. T. and Tian, M. Z. (2020). Foreign Trade, Technological Progress and Economic Growth: An Empirical Study Based on the Spatial Panel Simultaneous Equations. Journal of Applied Statistics and Management, 39(5), 771–787, (CSSCI, CSCD).
151. Tian, M. Z. and Mei, B. (2019). Tilting Quantile Regression Modeling of Functional Data and Its Applications. Statistical Research, 36 (8), 114 –128, (CSSCI).
152. Tao, L., Zhang, Y. J., and Tian, M. Z. (2019). Quantile Regression for Dynamic Panel Data Using Hausman-Taylor Instrumental Variables, Computational Economics, 53:1033–1069 (SSCI, SCI).
153. Dai, X. W., Jin, L. B., Tian, M. Z. and Shi, L. (2019). Bayesian Local Influence for Spatial Autoregressive Models with Heteroscedasticity. Statistical Papers, 60:1423–1446, (SCI).
154. Tian, Y. Z., Shen, S. L., Lu, G., Tang, M. L. and Tian, M. Z. (2019), Bayesian LASSO-Regularized Quantile Regression for Linear Regression Models with Autoregressive Errors, Communications in Statistics-Simulation and Computation, 48 (3): 777 –796, (SCI, EI).
155. Zhu, F. Y., Yue, T. Z., Wang, K., Liu, X. and Tian, M. Z. (2019). Application of Text Clustering Technique on Conan Doyle's Works. Journal of Applied Statistics and Management, 38 (5): 882 –898, (CSSCI, CSCD).
156. Hu, Y. N., Wang, C. Y. and Tian, M. Z. (2019). Variable Selection for Joint Modeling of Longitudinal Data and Survival Time. Journal of Applied Statistics and Management, 38(3), 483–494, (CSSCI, CSCD).
157. Hu, Y. N. and Tian, M. Z. (2019). Joint Modeling and Variable Selection for Zero-Inflated Count Data, Statistical Research, 36 (1): 104 –114, (CSSCI).
158. Wang, Y. R., Bai, Y. X. and Tian, M. Z. (2019). Tuning Parameter Selection Using ERIC Method in The Generalized Linear Model. Statistics & Information Forum, 34 (2), 19 – 27, (CSSCI).
159. Xia, L. L. and Tian, M. Z. (2019). Nonparametric Statistical Analysis of Zero-and-One Inflated Poisson Regression Models. Journal of Applied Statistics and Management, 38 (2), 235 – 246, (CSSCI, CSCD).
160. Xiong, W., and Tian, M.Z. (2019). Optimal Quantile and Its Applications in Reality. Applied Mathematics A Journal of Chinese Universities, 34 (1): 25– 43, (CSCD).
161. Xia, L. L., Tian, M. Z. and Zhu, Y. (2019). Construction of Confidence Intervals for the Whole Percentage Based on Saddle Point Approximations under Binomial Distribution. Statistics & Information Forum, 34(9): 3– 9, (CSSCI).
162. Cao, R. and Tian, M. Z. (2019). Mode Regression in the Secondary Analysis of Case-Control Data, Journal of Systems Science and Mathematical Sciences, 39(6): 954 – 976, (CSCD).
163. Yan, M. B. and Tian, M. Z. (2019). An Elastic Net Method Based on Variable Selection Events. Journal of Mathematics in Practice and Theory, 49 (12): 215– 226, (CSCD).
164. Mei, Y., Yan, M. B. and Tian, M. Z. (2019). The model of Customer Satisfaction and Its Application in the Study of the Relationship between College Student and Parentage, Journal of Mathematics in Practice and Theory, 49 (11): 78– 90, (CSSCI).
165. Tian, Y. Z., Wang, L.Y., Wu, X. Q. and Tian, M. Z. (2019). Gibbs Sampler Algorithm of Bayesian Weighted Composite Quantitle Regression. Chinese Journal of Applied Probability and Statistics. 35 (2), 178–192, (CSCD).
166. Wang, W. X. and Tian, M. Z. (2019). Confidence interval construction of correlation difference under saddle point approximation, Applied Mathematics A Journal of Chinese Universities, 34 (3): 264–272, (CSCD).
167. Tian, Y. Z., Tang, M. L., Wang, L. Y. and Tian, M. Z. (2019), Bayesian Bridge-randomized Penalized Quantitle Regression Estimation for Linear Regression Model with AP(q) Perturbation. Journal of Statistical Computation and Simulation, 89 (15):2951–2979, (SCI).
168. Xiong, W., and Tian, M. Z. (2019). Weighted Quantile Regression Theory and Its Application. Journal of Data Science,17(1). P. 145 - 160, (EI).
169. Zhang, R. X. and Tian, M. Z. (2019). Multivariate Outlier Detection Based on Tilting Minimum Covariance Determinant Method, Journal of Applied Statistics and Management, 38 (4): 619–627, (CSCD, CSSCI).
170. Tian, M. Z. (2018). Exact Exponential Risk Bounds for Conditional Quantile Regression. China Sciencepaper, 13(5), 598–610. (CSCD, CA, AJ, CSA, etc.).
171. Li, E. Q., Mei, B. and Tian, M. Z. (2018). Feature Screening Based on Ultrahigh Dimensional Competing Risks Models, SCIENTIA SINICA Mathematica，Vol. 48(8): 1061–1086.
172. Tian, Y. Z., Tang, M. L., Zang, Y. C. and Tian, M. Z. (2018), Quantile regression for linear models with autoregressive errors using EM algorithm, Computational Statistics. 33:1605–1625, (SCI).
173. Tian, Y. Z.,Yang, A. J., Li, E. Q. and Tian, M. Z. (2018). Parameters Estimation for Mixed Generalized Exponential Inverted Distributions with Type-II Progressive Hybrid Censoring. Hacettepe Journal of Mathematics and Statistics, 47 (4), 1023 –1039, (SCI).
174. Jiang, C. B., Wang, Z. and Tian, M. Z. (2018). Theory and Application of One-Side Kernel Estimation in Quantitative Financial Risk Management, Statistics Review, 10，100–121.
175. Bai, Y. X. and Tian, M. Z. (2018). Functional Analysis of Variance Based on Multiple Comparison Test, Statistics & Decision, 10, 62–56, (CSSCI).
176. Wang, C. Y. and Tian, M Z. (2018). The Iterative Generalized Least Squares Estimation for Multilevel Mixed Effects Model. Advances in Mathematics, 47(4)，613–623. (CSCD, CBST).
177. Li, E. Q. and Tian, M. Z. (2018). Construction of Fixed-width Confidence Intervals for Zero-Inflated Poisson Distributions Parameters. Chinese Journal of Applied Probability and Statistics, 34 (1): 49–74, (CSCD).
178. Mei, B. and Tian, M. Z. (2018). Analysis of Influencing Factors on PM2.5 in Beijing Based on Spatio-Temporal Model, Journal of Applied Statistics and Management, 37 (4): 571–586, (CSSCI, CSCD).
179. Wang, W. X. and Tian, M. Z. (2018). Evaluation of Economic Development in the Northern Slope Economic Belt of Tianshan Mountains Based on Principal Component Analysis, Journal of Mathematics in Practice and Theory, 48 (17), 71–78, (CSSCI).
180. Li, E. Q., Wu, Y. K. and Tian, M. Z. (2018), Joint Modeling for Generalized Hyperbolic Distributions, Journal of Mathematics in Practice and Theory, 48 (13), 152–162, (CSSCI).
181. Tai, L. N., Wang, C. Y. and Tian, M. Z. (2018). Inverse Probability Multiple Weighted Quantile Regression Estimation and Its Application with Missing Data. Statistical Research, 35 (9), 115-128, (CSSCI).
182. Su, P. and Tian, M. Z. (2018). Heteroscedasticity Detection and Estimation with Minimizing The Composite Quantile Loss, Journal of Systems Science and Mathematical Sciences, 38(9):1055–1066, (CSCD).
183. Tian, Y. Z., Tang, M. L. and Tian, M. Z. (2018). Joint Modeling for Mixed-effects Quantile Regression of Longitudinal Data with Detection Limits and Covariates Measured with Error, with Application to AIDS Studies. Computational Statistics, 33:1563–1587, (SCI).
184. Song, J., Li, E. Q. and Tian, M. Z. (2018). Analysis of Core Inflation Rate in China Based on SVAR Models. Statistics and Application, 2018, 7(6), 636–648, (RCCSE).
185. Li, E. Q., Qian, M. L. and Tian, M. Z. (2018). Fixed-Length Confidence Intervals for the Poisson Mean via Sequential Methods and Two-stage Methods. Journal of Systems Science and Mathematical Sciences, 38 (11), 1328–1346, (CSCD).
2017
186. Tian, M. Z. and Chan, N. H. (2017). Adaptive Quantile Regression with Precise Risk Bounds, Science in China Series A: Mathematics, 60 (5), 875–896, (SCI, EI).
187. Li, Z. Y., and Tian, M. Z. (2017). A New Method for Dynamic Stock Clustering Based Spectral Analysis. Computational Economics, 50 (3), 373–392， (SSCI, SCI).
188. Ma, C. T., Xiong, W. and Tian, M. Z. (2017). ROC Curve Based on Generalized Linear Mixed Effects Models in Repeated Diagnostic Tests, Chinese Journal of Health Statistics, 34 (1), 1–6, (CSCD).
189. Ma, C. X. and Tian, M. Z. (2017). Financial Impact Analysis for Urban-rural Income Gap in China based on panel quantile Regression. Journal of Applied Statistics and Management. 36(2), 341–350, (CSSCI, CSCD).
190. Zhang, T. T., Hu, Y. N., Li, Y. and Tian, M. Z. (2017). Feature Selection Based on Sparse Clustering with Application of China’s Environmental Problems. Statistics & Decision, 4, 18 – 24, (CSSCI).
191. Li, Z. Y. and Tian, M. Z. (2017). Detecting Change-point via Saddlepoint Approximations, Journal of Systems Science and Information, 5 (1), 48–73, (CSCD).
192. Meng, L. B., Li, E. Q. and Tian, M. Z. (2017). Confidence Intervals Construction for Odds Ratio under Binomial Sampling Based on Saddlepoint Approximation, Journal of Applied Statistics and Management, 36 (1), 85–102, (CSSCI, CSCD).
193. Tian, Y. Z., Lian, H. and Tian, M. Z. (2017). Bayesian Composite Quantile Regression for Linear Mixed-effects Models. Communications in Statistics – Theory and Methods, 46 (15), 7717–7731, (SCI, EI).
194. Xiong, W., Tian, M. Z. and Tang, M. L. (2017). Randomized Quantile Regression Estimation for Heteroscedastic Nonparametric Model. Communications in Statistics – Theory and Methods, 46 (10), 5147–5179, (SCI, EI).
195. Xu, L.W. and Tian, M. Z. (2017). Parametric bootstrap inferences for panel data models. Communications in Statistics – Theory and Methods, 46 (11), 5579 –5594, (SCI, EI).
196. Luo, J. and Tian, M. Z. (2017). Analysis of Air Quality Index Based on Negative Binomial Regression Models. Statistics & Information Forum, 32(7) 88–94, (CSSCI).
197. Ma, C. X., Tian, M. Z. and Pan, J. X. (2017). Semiparametric Hierarchical Model with Heteroscedasticity. Statistics and Its Interface, 10, 413–424, (SCI)
198. Bai, Y. X. and Tian, M. Z. (2017). Confidence Interval Construction for the Risk Difference of Chronic Disease Based on Saddle- point Approximation under Poisson Distribution. Applied Mathematics A Journal of Chinese Universities, 32(3) : 253–266, (CSCD)
199. Tian, Y. Z., Li, E. Q., Tian, M. Z. and Luo, Y. X. (2017). Quantile Regression for Censored Mixed Effects Models and Variable Selection. Acta Mathematica Sinica. 60 (2), 315–334, (CSCD).
200. Bai, Y. and Tian, M. Z. (2018). Comparison and Application of Several High Dimensional Variable Selection Methods, Statistics & Decision, 22, 11–16, (CSSCI).
201. Ma, C. X., Qian, M. L. and Tian, M. Z. (2017). Nonlinear Modeling of Heteroscedastic Hierarchical Data via ECM Algorithm. Acta Mathematica Sinica. 60 (5), 731–744, (CSCD).
202. Tao, L., Zhang, Y. J. and Tian, M. Z. (2017). Adaptive Penalty Quantile Regression for Panel Data. Journal of Systems Science and Mathematical Sciences, 37 (2), 609–622, (CSCD).
203. Hu, Y. N., Zhang, T. T., Li, L. and Tian, M. Z. (2017). Sparse VAR and Its Application to Stock Return. Journal of Applied Statistics and Management, 36 (4), 731–739, (CSSCI, CSCD).
204. Hu, Y. N., Yang, Y. Y., Wang, C. Y. and Tian, M. Z. (2017). Imputation in Nonparametric Quantile Regression with Complex Data. Statistics and Probability Letters, 127, 120–130, (SCI).
205. Tian, Y. Z., Han, X. F. and Tian, M. Z. (2017). Estimating Mixed Exponential Distributions Based on Hybrid Censored Samples. Chinese Journal of Applied Probability and Statistics, 33 (2), 191–202, (CSCD).
206. Tian, Y. Z., Qiu, X. P. and Tian, M. Z. (2017). Parameters Inference of Generalized Exponential Distribution Based on Generalized Progressively Hybrid Censoring Scheme. Chinese Journal of Applied Probability and Statistics, 33 (4), 369 – 384, (CSCD, CSSCI).
207. Hu, M. Y., Lin, X. F. and Tian, M. Z. (2017). The Study of the L Environmental Simulation Laboratory Quality System Assessment Index. Journal of Mathematics in Practice and Theory, 47(10), 17– 34, (CSSCI).
208. Wang, T. Y., Yang, Y. Q. and Tian, M. Z. (2017). Tuning Parameter Selection in Adaptive LASSO for Quantile Regression with Penal Data. Journal of Applied Statistics and Management, 36 (3), 429– 440, (CSSCI, CSCD).
209. Liang, X. L., Li, E. Q. and Tian, M. Z. (2017). The Parametric Estimation and Diagnostics of the Multivariate Generalized Poisson Distribution, Journal of Systems Science and Mathematical Sciences, 37(5), 1319–1334, (CSCD).
210. Wang, X. H. and Tian, M. Z. (2017). Analysis of Haze Counts Using Hierarchical Bayesian Spatiotemporal Models. Journal of Applied Statistics and Management, 36 (6), 970 – 982, (CSSCI, CSCD).
211. Wu, Y. K. and Tian, M. Z. (2017). An Effective Method to Reduce the Computational Complexity of Composite Quantile Regression. Computational Statistics, 32，1375 –1393, (SCI).
212. Zhu, Q. Q., Hu, Y. N. and Tian, M. Z. (2017). Identifying Interaction Effects Via Additive Quantile Regression Models. Statistics and Its Interface, 10, 255 – 265, (SCI).
213. Rong, Y. H., Tang, M. L. and Tian, M. Z. (2017). Longitudinal Data Analysis Based on Generalized Linear Partially Varying-Coefficient Models . Communications in Statistics – Theory and Methods, 46 (4), 1983 –2001, (SCI, EI).
214. He, X. S. and Tian, M. Z. (2017). Parameter Estimation of Binomial-Gumbel Mixed Compound Extreme Value Distribution, Statistics & Decision, vol. 11, 17–19, (CSSCI).
215. Tao, L., Zhang, Y. J. and Tian, M. Z. (2017). Adaptive Penalty Quantile Regression for Dynamic Panel Data. Journal of Systems Science and Mathematical Sciences, 37 (11), 2245–2259, (CSCD).
216. Bai, Y. X. and Tian, M. Z. (2017). Confidence Interval Construction for Quantile Residual Lifetime under Left-truncated and Right-Censored Data. Journal of Systems Science and Mathematical Sciences, 37 (12), 2412–2426, (CSCD).
217. Luo, Y. X., Tian, M. Z. and Li, H. F. (2017). The Research of Dual Regularized Quantile Regression for High Dimensional Mixed Effect Models. Statistical Research, 34 (7), 94–103, (CSSCI).
2016
218. Tian, Y. Z., Li, E. Q., and Tian, M. Z. (2016). Bayesian Joint Quantile Regression for Mixed Effects Models with Censoring and Errors in Covariates. Computational Statistics, 31(3), 1031–1057, (SCI).
219. Yan, Z. and Tian, M. Z. (2016). MCEM Estimation of Censored Linear Quantile Regression. Journal of Systems Science and Mathematical Sciences, 36(2), 145–156, (CSCD).
220. Wang, S., Wu, Y., W. and Tian, M. Z. (2016). An Analysis of the Influencing Factors of Price Determinants in Online Auction Based On Truncated Regression Models. Statistics and Application, 2016, 5(1), 1–8.
221. Liang, X. L. and Tian, M. Z. (2016). Empirical Study of the Relationship Between Chinese Listing Corporation Total Assets and Operating Income. Journal of Mathematics in Practice and Theory, 46 (9), 22–30, (CSSCI).
222. Hu, Y. N., Zhang, T. T. and Tian, M. Z. (2016). Variable Selection in Joint Modeling for Binary Response and Continuous Response. Statistics & Decision, 19, 4 – 8, (CSSCI).
223. Li, H. F., Luo, Y. X. and Tian, M. Z. (2016). The Research of Nonparametric Bayesian Regression for Mixed Effect Models. Statistical Research, 33 (4): 97–103 , (CSSCI).
224. Fan, Y., Tang, M. L. and Tian, M. Z. (2016). Composite Quantile Regression for Varying-Coefficient Single-Index Models. Communications in Statistics - Theory and Methods, 45 (10): 3027–3047, (SCI, EI).
225. Yan, Z. and Tian, M. Z. (2016). Change-point Analysis of CPI Based on Pruned Exacted Linear Time Method. Modern Management Science, 3, 18–20, (CSSCI).
226. Xia, W. T., Xiong, W. and Tian, M. Z. (2016). Heteroscedasticity detection and estimation with quantile difference method. Journal of Systems Science and Complexity, 29: 511–530, (SCI, EI, CSCD).
227. Tian, Y. Z., Tang, M. L.and Tian, M. Z. (2016). A Class of Finite Mixtures of Quantile Regression with Its Applications. Journal of Applied Statistics. 43, No. 7, 1240–1252, (SCI, SSCI)
228. Luo, Y. X., Li, H. F. and Tian, M. Z. (2016). The Research of Selecting Fixed and Random Effects Simultaneously Regression for Mixed Effect Models. Statistics and Decision. 15, 4 – 8, (CSSCI).
229. Wu, Y. K. and Tian, M. Z. (2016). An Analysis of Family SES Influence On Returns to Education Using UQR: Based On CGSS2010. Journal of Applied Statistics and Management . 35, No. 4, 692–699, (CSSCI, CSCD).
230. Yan, Z., Dai, X. W. and Tian, M. Z. (2016). Outliers Diagnosis in Big Data Levaraging Sampling. Journal of Applied Statistics and Management. 35, No.5, 794 – 802, (CSSCI, CSCD).
231. Huang, Y. L., Zhu, Q. Q. and Tian, M. Z. (2016). Nonparametric Quantile Regression with Censored Data. Journal of Biomathematics, 3, 387– 407, (CSCD).
232. Hu, Y. N., Zhang, T. T. and Tian, M. Z. (2016). A Spatial Quantile Regression Model for Local Fiscal Expenditure, Modern Management Science , 11, 18 – 20, (CSSCI).
233. Wang, J., Xiong, W. and Tian, M. Z. (2016). A Study on Allocation of Regional Education Resources of Beijing. Journal of Mathematics in Practice and Theory, 46(22), 65 – 72, (CSSCI).
234. Tian, Y. Z., Zhu, Q. Q. and Tian, M. Z. (2016). Estimation of Linear Composite Quantile Regression Using EM Algorithm. Statistics and Probability Letters. 117, issue C, 183 – 191, (SCI).
235. Qin, L., Xiong, W., and Tian, M. Z. (2016). Robust Modification of Leverage Importance Sampling for Big Data. Statistical Researach. 33 (8): 101 – 105, (CSSCI).
236. Mei, B. and Tian, M. Z. (2016). Bayesian Spatio-temporal Quantile Regression Model and Its Application for the Concentration of PM2.5 in Beijing, Statistical Research, 33 (12): 91-99 , (CSSCI).
237. Hu, Y. N., Zhang, T. T. and Tian, M. Z. (2016). Conditionally Parametric Quantile Regression Applied for Investment in Fixed Assets of National County Region. China Price, 10, 79 –81, (CSSCI)
238. Yang, C. L., Shuai, Y. X., Hu, X., Yang, R. and Tian, M. Z. (2016). Influence of Faculty Attitude on Wikipedia: Exploratory and Confirmatory Factor Analysis. Library Development, accept, 6–11, (CSSCI).
239. Luo, Y. X., Li, H. F., Tian, M. Z. and Zheng, L. (2016). Theoretical and empirical study on panel data models based on double penalized quantile regression. Journal of Wuhan University of Science and Technology. Vol.39, No.6, 462–467,（CSCD, EI）.
240. Bai, Y. X. and Tian, M. Z. (2016). Confidence Interval Construction for The Incidence of Chronic Diseases. Applied Mathematics A Journal of Chinese Universities, 31(2): 136–142, (CSCD).
241. Dai, X. W., Yan, Z. and Tian, M. Z. (2016). Estimation of Quantile Regression for the Panel Data Spatial Autoregressive Error Models With Fixed Effects. Acta Mathematicae Applicatae Sinica, 39(6), 847–858, (CSCD).
242. Xu, L.W. and Tian, M. Z. (2016). Tests for ANOVA models with a combination of crossed and nested designs under heteroscedasticity. Citation: AIP Conference Proceedings, Published by the American Institute of Physics, View online: http://dx.doi.org/10.1063/1.4952212, View Table of Contents: http://aip.scitation.org/toc/apc/1738/1, (CPCI-S, ISTP).
2015
243. Tian, M. Z. (2015). Several Hot Topics in Current Research of Statistical Theory of Big Data. Statistical Research, vol. 32 (5): 3–12, (CSSCI).
244. Zhao, Y. Y., Tian, M. Z., Wu, Y. K., Yan, Z, Dai, X. W., Hu, Y. N. and Li, E. Q. (2015). Reconstruction and Innovation of Statistics in the ERA of Big Data, Statistical Research, 32 (2): 3–9, (CSSCI).
245. Xiong, W. and Tian, M. Z. (2015). Simultaneous Variable Selection And Parametric Estimation for Quantile Regression. Journal of the Korean Statistical Society, 44, 134 – 149, (SCI).
246. Cao, S. R., Su, Y. N. and Tian, M. Z. (2015). Bayesian Inference and Applications in Hierarchical Models. Statistics & Decision, 423(3), 4–8, (CSSCI).
247. Si, S. J., Li, E.Q and Tian, M. Z. (2015). Semi-parametric Model with Bivariate Link Function. Chinese Journal of Contemporary Mathematics, 36, 173–190, (CSCD).
248. Wang, Z. and Tian, M. Z. (2015). Semiparametric Mode Regression Based on Locally Linear Additive Models. Statistical Review, Vol. 9, 124 –142.
249. Feng, D. D., Ma, C. X. and Tian, M. Z. (2015). Statistical Estimation of Multiple Poisson Rate. Journal of Probability and Statistical Science, 13(1), 53 – 68, (SCI).
250. Si, S. J., Li, E.Q and Tian, M. Z. (2015). Semi-parametric Model with Bivariate Link Function. Chinese Annals of Mathematics, 36A(2):191 – 208 ，(CSCD, CSSCI).
251. Wu, Y. K. and Tian, M. Z. (2015). Estimation of Spatial Quantile Autoregressive Model via EM Algorithm, Journal of Mathematics in Practice and Theory, 45 (11), 193–199, (CSSCI).
252. Tian, Y. Z., Zhu, Q. Q. and Tian, M. Z. (2015). Estimation for Mixed Exponential Distributions under Type-II Progressively Hybrid Censored Samples, Computational Statistics & Data Analysis, 89, 85–96, (SCI, EI).
253. Zhou, J., Fu, Z. N. and Tian, Y. Z. (2015). China transportation services index construction based on TSI index, Systems Engineering — Theory & Practice, 35 (4), 965–972, (CSCD, EI, CSSCI).
254. Meng, L. B. and Tian, M. Z. (2015). Saddlepoint Approximation to An Important Statistic Advances in Mathematics. 44 (5): 789–799 . (CSCD, CBST).
255. Chen, Y. L., Tang, M. L. and Tian, M. Z. (2015). Semiparametric Hierarchical Composite Quantile Regression. Communications in Statistics – Theory and Methods, 44 (5), 996 –1012, (SCI, EI).
256. Luo, J., Wang, X. H. and Tian, M. Z. (2015). Empirical Study of the Relationship Between Risk and Return of Chinese Stock Market Based on Quantile Regression. Statistics & Decision, 423, 121– 124, (CSSCI).
257. He, J., Xiong, W. and Tian, M. Z. (2015). Non-crossing Additive Qantile Curves and Its Applications to Housing Price. Journal of Applied Statistics and Management. 34 (4), 707–718, (In Chinese) , (CSSCI, CSCD).
258. Wu, Y. K. and Tian, M. Z. (2015). Improved Confidence Interval for the Risk Ratio under Inverse sampling. Journal of Systems Science and Mathematical Sciences. 35(10), 1168–1177， (CSCD).
259. Yan, Z. and Tian, M. Z. (2015). An Analysis of Effects of Automobile Exhaust on PM2.5 in Beijing Based on Quantile Regression. Statistics & Decision. 17, 103–105, (CSSCI).
260. Zhang, Y. J. and Tian, M. Z. (2015). A Qunatile Regession Approach for Estimating Panel Data Based on K-step Inferences, Journal of Systems Science and Mathematical Sciences 35(9), 1037– 1048, (CSCD)
2014
261. Xiong, W. and Tian, M. Z. (2014). Application of Quantile Regression Techniques in Linear Heteroscedastic Model. Statistics Review，8, 115–128, (CSSCI).
262. Xiong, W. and Tian, M. Z. (2014). A New Model Selection Procedure Based on Dynamic Quantile Regression. Journal of Applied Statistics, 41(10), 2240– 2256. (SCI, SSCI).
263. Xiong, W. and Tian, M. Z. (2014). A Novel Robust and Efficient Tool for Detecting Heteroscedasticity. Journal of Mathematics and Statistics, 10: 169–185.
264. Li, Z. Y., Su, Y. N. and Tian, M. Z. (2014). Analysis on Influencing Factors of National Images Based on Quantile Regression. Statistical Research. 31(8), 59–65, (CSSCI).
265. Li, Z. Y., Liu, S. B. and Tian, M. Z. (2014). Collective Behavior of Equity Returns and Market Volatility, Journal of Data Science, 12，545-562， (EI)
266. Chen, Y. L., Tian, M. Z. and Yu, K. and Pan, J. X. (2014). Composite hierarchical linear quantile regression. Acta Mathematicae Applicatae Sinica, English Serie, Vol. 30, 49–64, (SCI).
267. Liu, S. Q., Hu, Y. N. and Tian, M. Z. (2014). Longitudinal Data Analysis Based on Local Linear Quantile Regression. Statistics Review, 8, 149–162.
268. Yang, Y. Q. and Tian, M. Z. (2014). Noncrossing Quantile Regression Modelling for Regional Education Development Data in China. Statistical and Application. 3, 37–43.
269. Li, Z. Y., Liu, S. B. and Tian, M. Z. (2014). Momentum Effect Differs Across Stock Performances: Chinese Evidence. Acta Mathematicae Applicatae Sinica, English Series 30，278–288, (SCI).
270. Xiong, W. and Tian, M. Z. (2014). Robust Estimators of Scale Function. Journal of Systems Science and Mathematical Sciences. 34, 703–717， (CSCD).
271. Li, Z. Q, Tian, M. Z. and Luo, Y.X. (2014). Study on Adaptive Lasso Quantile Regression for Panel Data Models. Statistics & Information Forum, 29, 3–10, (CSSCI, RCCSE).
272. Tian, Y. Z., Tian, M. Z. and Zhu, Q. Q. (2014). Transmuted linear exponential distribution : a new generalization of the linear exponential distribution, Communications in Statistics - Simulation and Computation. 43, 2661–2677, (SSCI, SCI, EI).
273. Tian, Y. Z., Tian, M. Z. and Zhu, Q. Q. (2014). Inference for Mixed Generalized Exponential Distribution under Progressively Type-II Censored Samples. Journal of Applied Statistics. 41(3), 660–676 (SCI, SSCI).
274. Qian, Z. C., Zhang, C. Y., Meng, L. B. and Tian, M. Z. (2014). Confidence Intervals Construction for Epidemilogic Ralative Risk Under Binomial Sampling Based on Saddlepoint Approximation. Journal of Mathematics in Practice and Theory. 44, 204–217.
275. Tian, Y. Z., Tian, M. Z. and Zhu, Q. Q. (2014). Linear Quantile Regression Based on EM Algorithm, Communications in Statistics – Theory and Methods, 43: 3464–3484， (SCI, EI).
276. Tian, Y. Z., Tian, M. Z. and Zhu, Q. Q. (2014). Estimating a Finite Mixed Exponential Distribution Based on Progressively Type-II Censored Data, Communications in Statistics – Theory and Methods ，43: 3762–3776, (SCI, EI).
277. Tian, Y. Z. , Tian, M. Z. and Zhu, Q. Q. (2014). A new Generalized Linear Exponential Distribution and Its Applications, Acta Mathematicae Applicatae Sinica, English Serie , 30 (4)，1049 –1062 , (SCI).
278. Hu, Y. N., Zhu, Q. Q. and Tian, M. Z. (2-13). An Effective Technique of Multiple Imputation in Nonparametric Quantile Regression. Journal of Mathematics and Statistics. 10 (1): 30–44, 2014.
279. Fan, J. Y. Tang, M. L. and Tian, M. Z. (2014). Kernel Quantile Estimator with ICI Adaptive Bandwidth Selection Technique, Acta Mathematica Sinica, 30, 710–722. (SCI)
2013
280. Chen, Y. L. and Tian, M. Z. (2013). Comparative Study of Methods on Longitudinal Data Analysis. Statistics & Decision, 10， 23–26, (CSSCI).
281. Tian, Y. Z., Su, Y. N. and Tian, M. Z. (2013). Optimal Estimation of EXPAR model. Statistics Review.7，148–156. (CSSCI).
282. Li, H. F. and Luo, Y. X., Tian, M. Z. (2013). Bayesian Lasso Quantile Regression for Panel Data Models. The Journal of Quantitative & Technical Economics, 30 (2), 138-149. (CSSCI).
283. Guo, J., Tang, M. L., Tian, M. Z. and Zhu, K. (2013). Variable selection in high-dimensional partially linear additive models for composite quantile regression. Computational Statistics and Data Analysis. 65, 56–67. (SCI, EI).
284. Su, Y. N. and Tian, M. Z. (2013). Rolling Quantile Regression Model and Applications. Statistics Review. 7，124–135.
2012
285. Tian, M. Z. (2012). Robust Estimation in Inverse Problems via Quantile Coupling. Science in China Series A: Mathematics, 55 , 1029–1041. (SCI, EI, CCS, INSPEC, MR, Aerospace Database, MathSciNet, CA， etc.).
286. Tian, M. Z., Luo, Y. X., Su, Y. N., Fan, Y. and Han, J. L. (2012). Lack-of-Fit Tests Based on Weighted Ratio of Residuals and Variances. Journal of Systems Science and Complexity 25, 1202–1214. (SCI，EI).
287. Tian, Y. Z., Tian, M. Z. and Chen, P. (2012). Parameter Estimation for a Mixture of Generalized Exponential Distributions under Grouped and Right-Censored Samples, Chinese Journal of Applied Probability and Statistics, 28(6), 561–571. (CSCD), (CSSCI).
288. Tian, Y. Z. , Tian, M. Z. and Ran, Y. P. (2012). Parameters Estimation of Mixed Inverse Weibull Distributions Based on Grouped And Right-Censored Data. Statistics Review. 6, 82–90. (CSSCI).
289. Tian, Y. Z., Tian, M. Z. and Chen, P. (2012). Parameter Estimation of Mixed Exponential Distribution with Grouped and Right-Censored Data. Journal of Applied Statistics and Management, 31 (6), 981-989. (CSCD, CAJCED, CEPS, CJFD, CSSCI).
290. Tian, Y. Z., Tian, M. Z. and Chen, P. (2012). Parameters Estimation and Application of Generalized Exponential Distribution under Grouped and Right-Censored Data. Advances in Mathematics, 41(6), 755-762. (CSSCI).
291. Luo, Y. X., Lian H. and Tian, M. Z. (2012). Bayesian Quantile Regression for Longitudinal Data Model. Journal of Statistical Computation and Simulation, 82, 1635–1649, (SCI, SSCI).
292. Luo, Y. X., Tian, M. Z. and Li, H. F. (2012). A Note on Random Effects Growth Curve Models. Chinese Journal of Applied Probability and Statistics, 28(5), 520–534, (CSCD, CSSCI).
293. Zhang, Y. Y., Tang, M. L. and Tian, M. Z., (2012). Adaptive Quantile Regression Based on Varying-coefficient Models. Chinese Journal of Contemporary Mathematics, 33, 317–334. (CSSCI).
294. Guo, J., Tian, M. Z. and Zhu, K. (2012). New efficient and robust estimation in varying-coefficient models with heteroscedasticity. Statistica Sinica, 22, 1075–1101，(SCI, SSCI)
295. Shu, H., Feng, D. D. and Tian, M. Z. (2012). Improved Confidence Interval for The Number Needed to Treat Under Negative Binomial Sampling. Journal of Systematic Science and Mathematics, 32，1047-1056， (CSSCI).
296. Zhang, Y. Y., Tang, M. L. and Tian, M. Z., (2012). Adaptive Quantile Regression Based on Varying-coefficient Models. Chinese Annals of Mathematics, 33A(5): 539–556, (CSCD, CSSCI)
297. Tian, M. Z., (2012) . The Sentiment of Teaching Methodology in One's Lecturing Life. University Teaching Quality Quarterly, 3: 44–46.
2011
298. Luo, Y. X., Li, H. F. and Tian, M. Z. (2011). Quantile Regression for Panel Data Based on Gibbs Sampling Algorithm. Statistical Research. 28, (7): 98–103, (CSSCI).
299. Tian, M. Z. et al. (2011) Abstract of the International Statistics Forum of 2010. Statistics & Information Forum. 26, 60–111.
300. Su, Y. N. and Tian, M. Z. (2011). Adaptive Local Linear Quantile Regression, Acta Mathematicae Applicatae Sinica (English Series). 27, 509–516, (SCI) .
301. Zhou, P. P. and Tian, M. Z. (2011). Multiple-day VaR calculating rules in financial risk management. The 8th International Conference on Service Systems and Service Management (ICSSSM’11） June 25–27, 2011 Tianjin, China . (EI).
302. Li, Z. Y., Liu, S. B and Tian, M. Z. (2011). Macro-stress testing of credit risk for Chinese banking sector: two comparative approaches. The 8th International Conference on Service Systems and Service Management (ICSSSM’11), June 25–27, 2011 Tianjin, China. (EI)
2010
303. Tian, M. Z., Chan, N. H. (2010). Saddle Point Approximation and Volatility Estimation of Value-at-Risk, Statistica Sinica, 20, 1239—1256, (SCI, SSCI)
304. Luo, Y. X. and Tian, M. Z. (2010). Quantile regression for panel data and its simulation study. Statistical Research. 27, (10): 81–87, (CSSCI).
305. Luo, Y. X. , Tian, M.Z. and Zhang, J.Y.(2010), An adaptive wavelet de-noising method based on quantile coupling, The 2nd International Conference on Image Analysis and Signal Processing, Xiamen, 109–112. (SCI/SSCI/A&HCI)
306. Zhao, Y. Y., Li, J. P. and Tian, M. Z. (2010). Stride toward the frontiers of the international statistical research, promote the reform and development of statistics–4th International Forum on Statistics, Renmin University of China and 5th International Symposium on Frontier of Statistical Science, Statistical Research. 27, (10): 88–112, (CSSCI).
307. Dai, C., Chen, B.Y. and Tian, M.Z. (2010). Bayesian Inference for the Probability of Contagious Negative Binomial distribution. Statistics & Decision, 6, 7–9, (CSSCI).
308. Chen, D. Q. and Tian, M. Z. (2010). A Comparison of Several Different Approaches in Sliced Inverse Regression. 4, 8–10, Statistics & Decision, (CSSCI).
309. Tang, M. L. and Tian, M. Z. (2010), Approximate confidence interval construction for risk difference under inverse sampling. Statistics and Computing. 20，87–98 (SCI, EI).
310. Luo, Y. X. and Tian, M. Z. (2010). Quantile regression for panel data and its simulation study. Statistics and Actuarial Science. 1, 3–10, (CSSCI).
2009
311. Tian, M. Z., Tang, M. L., Ng, H. K. T. and Chan, P. S. (2009), A comparative study of confidence intervals for negative binomial proportion. Journal of Statistical Computation and Simulation. 79, 241–249 (SCI, SSCI)
312. Tang, M. L. and Tian, M. Z. (2009), Asymptotic interval estimation of risk difference under inverse sampling Computational Statistics and Data Analysis，53, 621–631. (SCI)
313. Fan, J. Y. and Tian, M. Z. (2009), A new index of goodness-of-fit tests for hierarchical linear models, Statistics & Decision，21，16–19, (CSSCI).
314. Tian, M. Z., Tang, M. L., and Chan, P. S. (2009), Semiparametric quantile modelling of hierarchical data. Acta Mathematica Sinica , 25, 597–616 , (SCI)
2008
315. Tang, M. L., Tian, M. Z.and Chan, P. S. (2008), On the bootstrap quantile-treatment-effect test. Journal of Applied Statistics. Vol. 35 (1), 335–350. (SCI, SSCI).
316. Tian, M. Z., Tang, M. L., Ng, H. K. T. and Chan, P. S. (2008), Confidence interval estimators for risk ratio under inverse sampling. Statistics in Medicine. 27: 3301–3324, (SCI).
317. Wu. X. and Tian, M. Z., (2008), A longitudinal study of the effects of family background factors on mathematics achievements using quantile regression. Acta Mathematicae Applicatae Sinica (English Series). 24(1), 85–98. (SCI)
318. Zhong, Y. and Tian, M. Z. (2008) Bayesian analysis of change-point problems in rare events. Statistics & Decision. Vol. 3, 38–43. (In Chinese), (CSSCI).
319. Luo, Y. B., Tian, M. Z.and Wu, X. Z., (2008) Saddlepoint approximations to generalized chi-squared mixed distributions. Statistics & Information Forum, Vol. 1, 29–31. (In Chinese), (CSSCI).
320. Tian, M. Z., Wu, X., Li, Y. and Zhou, P. (2008), Longitudinal study of the external pressure effects on children’s mathematics and science achievements using nonparametric quantile regression. Chinese Journal of Applied Probability and Statistics. 24, 327–336. , (CSSCI).
321. Tian, M. Z., Wu, X., Li, Y., and Zhou, P. (2008), Approximate and asymptotic confidence intervals for epidemiologic rate under inverse sampling. Journal of System Science and Mathematical Science. 28, 513–523, (CSSCI).
322. Tian, M. Z., Wu, X. Li, Y. and Zhou, P. (2008), An analysis of mathematics and sciences achievements of American youth with nonparametric quantile regression. Journal of Data Science, 6, 449–465, (CSSCI).
2007 (Omitted)
2006
323. Tian, M. Z. and Chen, G. M. (2006), Quantile-hierarchical models. Science in China Series A: Mathematics, 36(10), 1103–1118. (In Chinese), (CSSCI).
324. Tian, M. Z. (2006), A quantile regression analysis of family background factor effects on mathematical achievements, Journal of Data Science, 4, 461–478, (EI).
325. Tian, M. Z. and Chen, G. M. (2006), Hierarchical linear regression models for conditional quantiles. Science in China Series A: Mathematics, 49, 1800–1815. (SCI, EI)
326. Tian, M. Z. (2006), Two stages inferences for a semi-parametric regression model. Acta Mathematicate Applicate Sinica, 29， 601–608, (CSSCI).
2005
327. Tian, M. Z. (2005), Extreme distribution of the weighted sum of a class of $m$ dependent stochastic variable sequences. Math. Theory Appl. 25, 5–9, (CSSCI).
328. Tian, M. Z. (2005), Estimation theory based on quasi-residuals in sliced inverse regression, Journal of Systems Science and Mathematical Sciences, 25, 348–355, (CSSCI).
2004
329. Tian, M. Z. and Li, G. Y. (2004), Quasi-residuals method in sliced inverse regression, Statistics and Probability Letters, 66, 205–211. (SCI)
2003
330. Tian, M. Z. and He, C. Z. (2003), A generalized variance-ratio test for a Heteroskedastic regression, Mathematics in Economics, 20, 52–61, (CSSCI, CSCD).
2002
331. Tian, M. Z. and Wu, X. Z. (2002), On an extended quasi-likelihood estimation and a diagnostic test for heteroscedasticity in the generalized linear models. Mathematical Theory and Applications, 22, 5–14, (CSSCI).
2001
332. Tian, M. Z. and Wu, X. Z. (2001), A quasi-residuals method, Advances in mathematics, 30, 182–184, (CSSCI, SCI).
333. Tian, M. Z. and He, C. Z. (2001), Quasi-residual diagnostic theory and methodology for heteroscedastic model, Natur. Sci. J. Xiangtan Univ. 23, 1–8.
2000
334. Tian, M. Z. (2000), The limiting property of error variance in a semi-parametric errors-in-variances model, Journal of Hunan University, 27, 4–9.
Papers under review
335. Zhou, P. P., Li, J. and Tian, M. Z. (2012). Empirical studies of the dynamic effects of China's price level based on SVECM, Statistical Research. (under review), (CSSCI).
336. Si, S. J., Pan, J. X. and Tian, M. Z. (2012). Robust Estimation for Joint Mean-Variance Models. (under review)
337. Tian, M. Z., Zhang, H. P. (2012). Parametric Modeling for Complex Large-scale Genetic Data Sets with Multiple Ordinal Traits, (Submitted), (SCI).
338. Tian, M. Z. (2012). Locally Adaptive Quantile Regression And Its Applications, Journal of the American Statistical Association. (No. JASA-T10-045 ), Under revision. (SCI)
339. Han, J. L., Pan, J. X. and Tian, M. Z. (2012). Parameters estimation in nonlinear reproductive dispersion mixed models. (Under revision：No. 10109).
340. Tian, M. and Härdle, W. (2012). Locally varying bandwidth selection for conditional quantile regression. (Under review).
341. Tian, M. Z. and Chen, G. (2010). A limit distribution for the maximum of weighted sums of m-dependent random variables. (Under review).
342. Feng, D. D. and Tian, M. Z. (2013). Nonparametric quantile regression with censored data. (Under review)
343. Li, Q. and Tian, M. Z. (2013). Locally smoothing composite quantile regression based on semiparametric models. (Under review)
344. Lv, S and Tian, M. Z. (2013). Generalized varying coefficient mean covariance regression methods for longitudinal data. (Under review)
345. Chen, Z. Q., Tang, M. L. and Tian, M. Z. (2013). Efficient weighted composite quantile regression with ignorable missing values and the oracle model selection theory. (Under review)
346. Tian, Y. Z. and Tian, M. Z. (2013). Censored Quantile Regression for Longitudinal Mixed Effects Models and Variable Selection. Statistical Sinica, (No. SS-13-293)
347. Xiong, W., Tian, M.Z. and Tang, M. L. (2012). Dynamic quantile regression estimation for heteroscedastic nonparametric models, Annals of Statistics, (No. AOS1304-012), (SCI)
348. Xiong, W. and Tian, M.Z. (2014). Reweighted efficient estimation in varying coefficient models (SCI)
349. Tian, Y. Z. and Tian, M. Z. (2014). Censored quantile regression of mixed effects models with measurement error in covariates, Scandinavian Journal of Statistics. (SCI)
350. Tian, Y. Z. and Tian, M. Z. (2014). Estimating Mixed Exponential Distributions under Hybrid Censoring , Scandinavian Journal of Statistics. (SCI)
351. Li, E. Q. and Tian, M. Z. (2014). Hierarchical Spline Models for Conditional Quantiles and the Air Quality Index of Beijing. (CSSCI).
352. Liang, X. L. and Tian, M. Z. (2014). The Estimation of Epidemiological Rate under Inverse Sampling Estimation Based on Hierarchical Models, under review, (CSSCI).
353. Yuan, M. and Tian, M. Z. (2014). Yuan, M. and Tian, M. Z. (2014). Quantile Regression Analysis of Monetary Policy Effect on Inflation, under review, (CSSCI).
354. Shi, P. X. and Tian, M. Z. (2014). Empirical Analysis of Chinese Urban and Rural Residents’Deposit Influential Factors Based on Quantile Regression, under review, (CSSCI).
355. Xiong, W. and Tian, M. Z. (2014). A New Robust Regression Method Based on Sparsity Function, under review, (SCI).
356. Li, E.Q. and Tian, M. Z. (2014), Hierarchical Spline Models for Conditional Quantiles and The Air Quality Index of Beijing, under review, (SCI).
357. Yang, Y. Q. and Tian, M. Z. (2014), Quantile Regression Based on Single Index Models for Longitudinal Data, under review, (CSSCI).
358. Ma, C. T and Tian, M. Z. (2014), Nonlinear Mixed Effects Model of ROC and Its Medical Applications, under Review, (CSSCI).
350. Tian, M. Z., Tang, M. L., and Chan, P. S. (2010). Saddlepoint approximations to conditional probability integral in metal analysis. (Under review).
360. Tian, M. Z. (2010). A limit distribution for the generalized Erdös-Kac Statistic. (Under review)
361. Meng, L. B. and Tian, M. Z. (2015). Semi-parametric Nonlinear Mixed Effects Models Based on Saddlepoint Approximation, (SCI).
362. Tian, M. Z. (2015). Several Hot Topics In Current Research of Statstical Theory of Big Data Statistical Research, 2014–1617 , (CSSCI).
363. Wu, Y. K. and Tian, M. Z. (2016). A Novel Competitive Approach for Intervals of The Difference Between Independent Binomial Proportions, Computational Statistics, COST-D-18-00217, under review, (SCI)
364. Tian, Y. Z., Han, X. F. and Tian, M. Z. (2015). Estimating Mixed Exponential Distributions under Hybrid Censoring , Statistical Methodology . (SCI)
365. Mei, Y., Li, E. Q. and Tian, M. Z. (2015). A Study of the Internet-based Community Management Based on Factor Analysis and Quantile Regression. Statistics and Decision. Under review, (CSSCI).
366. Cao, Z. Z., Yan, Z. and Tian, M. Z. (2015). An Analysis of Factors Influencing the Price of Real Estate in Beijing Based on Regression Tree. Under review, (CSSCI).
367. Yuan, M. and Tian, M. Z. (2015). State Space Mixed Model for Negative Binomial Responses. Under review, (CSSCI).
368. Shi, P. X. and Tian, M. Z. (2015). Bayesian Inference for Dynamic Zero-inflated Poisson Model. Under review, (CSSCI).
369. Meng, L. B. and Tian, M. Z. (2015). Confidence Intervals Construction for Odds Ratio under Binomial Sampling Based on Saddlepoint Approximation. Under review, (CSSCI).
370. Yang, Y. Q., Yan, Z.,Tian, M. Z. and Pan, J. X. (2019). Variable Selection in Joint Modeling for Longitudinal Multiple Outcomes. SCIENCE CHINA Mathematics, SCM-2020-0104, (SCI).
371. Zhang, Y. L. and Tian, M. Z. (2016). Parameter Estimation of Zero-Inflated Poisson Model Based on Probit Regression. Statistical Review.
372. Hu, Y. N. and Tian, M. Z. (2016). Modeling for Zero-Inflated Data via EM Adaptive Elastic Net. Journal of Statistical Computation and Simulation, GSCS-2016-0735, (SCI).
373. Zhang, Y. J., Li, L. and Tian, M. Z. (2015). Research On ELES Model Based On The Theory of Habit Formation and Dynamic Panel Quantile Regression, Chinese Annals of Mathematics, Series A. (CSSCI)
374. Yan, Z., Dai, X. W. and Tian, M. Z. (2015). A New Effective Sampling Algorithm Based on M-distance for Big Data. Statistical Papers, No. STPA-D-16-00396, (SCI).
375. Luo, Y. X., Li, H. F. and Tian, M. Z. (2015). The Research of Bayesian Double Penalized Quantile Regression for Mixed Effects Models and Its Simulation Studies. Journal of Mathematics in Practice and Theory.
376. Tian, Y. Z., Luo, Y. X. and Tian, M. Z. (2015). Censored Quantile Regression for Longitudinal Mixed Effects Models and Variable Selection. Acta Mathematica Sinica, English Series，B20150507, (SCI).
377. Tang, M. L., Tian, M. Z. and Tian, Y. Z., (2016). Mixed-effects Quantile Regression Model for Longitudinal Data with Detection Limits and Covariates Measured with Error, with Application to AIDS Studies. Statistics and Computing, ID: STCO-D-16-00142, (SCI).
378. Dai, X. W., Li, S. Y. and Tian, M. Z. (2019). Quantile Regression for Partially Linear Varying Coefficient Spatial Autoregressive Models. Journal of Applied Statistics, No. CJAS-2019-0650，(SSCI).
379. Gu, M. C. and Tian, M. Z. (2016). Periodic Spatial-Temporal Quantile Model with Varying Coefficients, Computational Statistics, No. COST-D-17-00325, (SCI).
380. Yuan, B. and Tian, M. Z. (2016). Mixed Copula Based on Empirical Distribution and Its Applications to Financial Risk Management , Statistical Research, (CSSCI).
381. Qian, M. L. and Tian, M. Z. (2016). Analysis on Influencing Factors of PM2.5 in Beijing Based on Quantile Regression, Forcasting, (CSSCI).
382. Wang, S. and Tian, M. Z. (2016). A Non-linear Hierarchical Growth Curve Model for Forecasting the Outstanding Claims Reserves, Economic Management Journal，(CSSCI).
383. Zhang, W. S. and Tian, M. Z. (2016). Statistical Analysis of the Survival Rule of Electrical Vehicles, Statistics & Information Forum, , (CSSCI, RCCSE).
384. Luo, Y. X., Li, H. F. and Tian, M. Z. (2016). The Theoretical and Empirical Study of Panel Data Models Based on Double Penalized Quantile Regression. Technology Economics.
385. Yan, Z. and Tian, M. Z. (2016). A Novel Testing Tool for Heteroscedasticity Using Double Kernel Approach. Test, SEIO-D-16-00138, (SCI).
386. Ao, Y. H., Zhang, H. L., Zhang, Z., Yan, X., Shen, G. J., Liang, Q. J. and Tian, M. Z. (2016). The Analysis of Value Investment Based on Discriminant Approach. The Theory and Practice of Finance and Economics, (CSSCI)
387. Li, P. S., Zhan, T. H., Huang, X., Zhao, H. Z., Liu, Y. Z. and Tian, M. Z. (2016). Analysis on the Characteristics of Poverty Counties in Henan Province Based on Multidimensional Scaling. Henan Social Sciences, (CSSCI).
388. Li, X., Zhao, S. Y., Zhang, X. Y., Liang, Y., Yang, Z. H., and Tian, M. Z. (2016). Relationship between Regional Development and Sex Discrimination Based on Canonical Correlation Analysis. Population and Development, (CSSCI)
389. Wang, J. Q., Zhang, W. L., Wang, Y., Yi, M. Z. and Tian, M. Z. (2016). Research on Consumer Behavior Based on the Joint Analysis Method-An Example of the Purchase Preference of Ice Cream. Advances in Psychological Science, (CSCD, CSSCI)
390. Li, C. X., Han, Z. K, Shi, B. H., Song, Y. and Tian, M. Z. (2016). Empirical Analysis of Stock Market Forecast Based on Support Vector Machine. Modern Management Science, (CSSCI).
391. Sun, W. B., Wang, L. and Tian, M. Z. (2016). The Determinants of Resident Income Based on Classification Trees. Economic Review, (CSSCI).
392. Sun, Q. H., Wang, Y. L., Zhou, Z. Y., Li, Z. F., Zhou, Z. F. and Tian, M. Z. (2016). An Empirical Study on the Economic Differences between the Provinces in China Based on the Principal Component Analysis. Statistical Research, (CSSCI).
393. Zou, W. C., Zheng, Q., Qiao, Y. F., Wu, J. P., Huang, W. H. and Tian, M. Z. (2016). An Empirical Study on the Economic Differences between the Provinces in China Based on the Principal Component Analysis. Journal of Industrial Engineering and Engineering Management, (CSSCI).
394. Mei, B. and Tian, M. Z. (2016). Tilting Quantiles for Functional Data Based on Sparse Smoothing, Biometrika, No. BIOMTRKA-16-478, (SCI).
395. Mei, B. and Tian, M. Z. (2016). Linear Tilting Quantile Regression for Functional Data Using Sparse Smoothing. Journal of the Royal Statistical Society –Series B, (ID: JRSS-OA-SB-Nov-16-0507, (SCI).
396. Wang, C. Y. and Tian, M. Z. (2016). Variable Selection via Adaptive Group Lasso in Additive Quantile Regression Models. No. JSPI-D-16-00592 , Journal of Statistical Planning and Inference, (SCI).
397. Tian, Y. Z., Wu, X. Q., and Tian, M. Z. (2016). A Gibbs Sampling Algorithm For Bayesian Weighted Composite Quantile Regression. Journal of the Korean Statistical Society, under review, (SCI).
398. Hu, Y. N., Wang, C. Y. and Tian, M. Z. (2017).The Application of Sparse VARX Model in Analyzing Agricultural Commodity Domestic Prices. The Journal of Quantitative & Technical Economics, No.20170520004, under review (CSSCI).
399. Tian, Y. Z., Tang, M. L., Wang, L. Y. and Tian, M. Z. (2017), MCMC Algorithm of Bayesian Weighted Composite Quantile Regression, Acta Math Sinica, (No.B20170358), under review, (SCI).
400. Tian, X. T. and Tian, M. Z. (2018). Tests for Sphericity and Identity of High-Dimensional Covariance Matrices, Chinese Annals of Mathematics, Seriers A, (No. ), (CSCI).
401. Xiong, W. and Tian, M. Z. (2014). Hybrid Weighted Quantile Regression, Journal of Applied Statistics , No. CJAS-2017-0918, under review, (SCI).
402. Li, E. Q., Dai, X. W. and Tian, M. Z. (2016). Variable Selection Based on Ultrahigh Dimensional Competing Risks Models. , (No.) , ( ).
403. Tian, M. Z. and Härdle, W. (2017). Exponential Risk Bounds and Locally Adaptive Varying Bandwidth Selection for Conditional Quantile Regression, Bernoulli Journal, BEJ1503–029, under review, (SCI).
404. Tao, L., Qian, M. L. and Tian, M. Z. (2018). A Two-stage Approach to Instrument Variable Quantile Regression for Group-level Treatments. Journal of Systems Science and Mathematical Sciences, (No. ), under review, (CSCD) .
405. Xia, L. L. and Tian, M. Z. (2018). Employee Turnover Forecast Based on Lasso-Logistic Regression Model. Statistics & Information Forum, No. , -. under review, (CSSCI).
406. Yan, M. B. and Tian, M. Z. (2018). Two Points of Innovation Analysis on the Improvement of the Statistical System in the New Era. China Statistics, No. , under review, (CSSCI).
407. Bai, Y. X., Qian, M. L. and Tian, M. Z. (2019). Double-penalized Quantile Regression in High Dimensional Partially Linear Additive Models. Journal of the Korean Statistical Society, No. JKSS-D-19-00138, under review, (SCI).
408. Tao, L., Tai, L. N. and Tian, M. Z. (2018). Interconnected Financial Risk Control Based on Statistical and Data Science's Perspective. China Finance, No. , under review, (CSSCI).
409. Li, T. T. and Tian, M. Z. (2018). Using Hybrid Volatility’s CAViaR Model for Value-at-Risk, Statistics and Information Forum, No. 2018.10.0106, under review, (CSSCI).
410. Liu, Y. J. and Tian, M. Z. (2018). The Method of Principle Component for Functional Data and Its Application to the Estimation of Volatility of Stock. Statistical Research, No. 2018-1294, (.),—, under review, (CSSCI).
411. Yu, Y. and Tian, M. Z. (2018). Prediction of Popularity of Articles in Social Networks - based on Estimation of Generalized Linear Models with Imputed Data. Forecasting, (.),—, under review, (CSSCI).
412. Zhang, Y. X., Meng, S. W. and Tian, M. Z. (2019). Optimal Bonus-Malus Systems for Automobile Insurance under the Assumption of Conjugate Prior Distributions, ASTIN Bulletin - The Journal of the International Actuarial Association, No. ASTIN-2019-01-008, under review, (SSCI).
413. Rui, R. X. and Tian, M. Z. (2019). A Novel Quantile Test Based on Percentile Deviation. Chinese Annals of Mathematics, _A(2): – ，(CSCD, CSCI).
414. Tai, L. N., Tao, L. and Tian, M. Z. (2020). Bayesian Semiparametirc Quantile Sample Selection Model with Heterogeneity, Acta Mathematica Sinica , (.),–, , (SCI).
415. Zhang, R. X. and Tian, M. Z. (2019). Sliced Inverse Quantile-based Regression for Dimension Reduction, Journal of…, , under review, (SCI).
416. Su, P. and Tian, M. Z. (2019). Censored Quantile Correlation Screening, Biometrics , No. BIOM2019679M , under review, (SCI).
417. Dang, L. X. and Tian, M. Z. (2019). Research on Multi-Classification Problem for Imbalanced Data Based on Active Learning and Boosting Algorithm, Journal of…, , under review, (CSSCI).
418. Han, Z. K. and Tian, M. Z. (2019). Research on Fraud Detection Models in Third Party Payment, Journal of…, , under review, (CSSCI).
419. Li, E. Q., Dai, X. W. and Tian, M. Z. (2019). Penalized Weigted Competing Risks Models Based on Quantile Regression, Journal of …, , under review, (SCI).
420. Ma, S. P. and Tian, M. Z. (2019). Research on Financial Distress Early-warning of Listed Companies Based on Regularized Logit Mixed Effect Model. Journal of…, , under review, (CSSCI).
421. Yan, M. B. and Tian, M. Z. (2019). The Oracle Properties of Adaptive Lasso under Selective Inference Scheme. Journal of…, , under review, (CSCD).
422. Bai, Y. X., Tang, M. L. and Tian, M. Z. (2019). Variable Selection for High Dimensional Additive Non-linear Interaction Model under Marginality Principle. , No. , under review, (SCI).
423. Wang, W. X. and Tian, M. Z. (2020). Bayesian Quantile Regression and Its Applications in Generalized Linear Mixed Effects Models, Journal of Systems Science and Mathematical Sciences, , (CSCD).
424. Zhang, C. L. and Tian, M. Z. (2019). Construction of Bootstrap Confidence Intervals Based on Bayes. Statistics and Decision, No. 190715011, to appear, (CSSCI).
425. Luo, Y. X., Zhang，M. and Tian, M. Z. (2019). Research of Additive Quantitle Regression Model for Panel Data and Its Application. Statistical Research, …, –, under review, (CSSCI).
426. Rui, R. X. and Tian, M. Z. (2019). Parameter Estimation in Multi-response Multivariate Generalized Linear Models with Cross-Sectional Data. Journal of Multivariate Analysis, JMVA_2019_359 , under review, (SCI).
427. Xia, L. L. and Tian, M. Z. (2019). Semiparametric Regression Analysis for a Class of Constrained Zero-Inflated Generalized Poisson Models. Journal of Statistical Computation and Simulation, No. GSCS-2019-0488, (SCI).
428. Liu, Y. and Tian, M. Z. (2019). Economic Development Analysis of Counties (Cities) Directly under Yili Prefecture Based on Correspondence Analysis, Economic Review, No. …, under review, (CSCD).
429. Rui, R. X., Liu, Y. X., Wang, Y. H. and Tian, M. Z. (2019). Parameter Estimation in Multi-response Multivariate Generalized Linear Models with Cross-Sectional Data. Journal of Applied Statistics and Management, No. – , under review, (CSSCI, CSCD).
430. Luo, Y. X., Zuo, Q. and Tian, M. Z. (2019). Unconditional Quantile Regression for Panel Data with Fixed Effects and Its Application. The Journal of Quantitative & Technical Economics, under review, (CSSCI).
431. Mu, J. and Tian, M. Z. (2020). Adaptive Group Lasso Penalty Quantile Regression Method for High Dimensional Change Point Model. Journal of Systems Science and Mathematical Sciences, No. 20096, under review, (CSSCI).
432. Li, C. Y. and Tian, M. Z. (2019). Resampling Algorithm Based on Algorithmic Leveraging in Big Data Analytics. Statistical Research, under review, (CSSCI).\
433. Zhang, Y. X., Meng, S. W., and Tian, M. Z. (2020). Cost Analysis of Insurance Companies Based on Semiparametric Hierarchical Quantile Regression Model. Insurance Studies, No. 2020. 01. 04. 0002, under review, (CSSCI).
434. Hou, J. and Tian, M. Z. (2020). Study on the Influencing Factors of Commodity Housing Price Based on Improved GTWR model - Taking Urumqi as An Example. Journal of Mathematics in Practice and Theory, No. , (CSSCI, CSCD).
435. Liu, Y., An, B. W. and Tian, M. Z. (2020). Likelihood Test and Its Statistical Inference Based on Zero-one Expansive Poisson Model. Statistics & Information Forum, No. 2020.03.0210, under review, (CSSCI).
436. Rui, R. X. and Tian, M. Z. (2020). A Study of the Impact of the Brexit for the Economy of the European Union and the United Kingdom. Economic Research Journal, No. , under review, (CSSCI).
437. Xiong, W. and Tian, M.Z. (2020). An Innovated Attributes-Benefit Latent Space Model for Directed Scale-Free Networks, Social Networks, (1): – , (SCI).
438. An, B. W., Hou, Z. M., Liu, Y. and Tian, M. Z. (2020). Statistical Diagnosis and Confidence Interval Construction of Zero-inflation Poisson Regression Model, Journal of Applied Statistics and Management, under review, (CSSCI, CSCD).
439. Liang, J. W. and Tian, M. Z. (2020). l_0 Penalized Quantile Regression. Journal of Computational and Graphical Statistics, No. JCGS-20-248, under review, (SCI).
440. Tian, Y. Z. Tang, M. L. and Tian, M. Z. (2020). Bayesian Joint Regularized Quantile Regression Inference for Multi-Response Linear Regression Model.
441. Liang, J. W. and Tian, M. Z. (2020). Imputed Tensor Regression for Spatial-temporal Data. Journal of Multivariate Analysis, JMVA_2021_, under review, (SCI).
442. Hu, Y. N., Qu, X. H., Wolfgang, H. K. and Tian, M. Z. (2021). Smoothed GMM for Spatial Autoregressive Quantile Modes, Journal of Business & Economic Statistics, No. JBES-P-2023-0704: –, (SSCI).
443. Wang, K., Zhao, S., Tian, M. Z., Yu, Z. X., He, D. H., Yang, L. P., Shang, H., Wang, C. X., Zeng, T., Zhang, L. P., Wang, X. D., Zhou, P., Wu, X. F., Wang, M. H., Wang, W. M., Cai, Y. L., Qin, J, Ran, J. J. and Zhang, X. L. (2021). Modelling the Time Interval between Transmission Generations and the Presymptomatic 2 Period of COVID-19 by Using Contact Tracing Surveillance Data from 100 Cities in Mainland China. Respiratory Research, , –, (SCI).
444. Qian, Z., Luo, Y. X., Zhao, X. Y. and Tian, M. Z. (2021). ….. Journal of Applied Statistics and Management, , –, (CSSCI, CSCD).
445. Meng, L. J., Kurbanyaz, G. and Tian, M. Z. (2021). Statistical Analysis of Chinese Covid-19 Epidemic Data Based on Bayesian-INLA. Journal of Systems Science and Mathematical Sciences, under review, (CSSCI).
446. Zhang, L. P., and Tian, M.Z. (2021). Research on Evaluation of Competitiveness Level of Xinjiang Catering Industry, Journal of Mathematics in Practice and Theory, under review (CSCD).
447. Si, S. J., Gu, J. W., and Tian, M.Z. (2021). Leveraging Single-case Results to Bayesian Hierarchical Modelling, Computational Statistics and Data Analysis, under review (CSCD).
448. Kurbanyaz, G, and Tian, M.Z. (2021). Statistical Diagnosis of Joint Log Mean and Log Variance Model Under Lognormal Distribution, Statistical Research, under review (CSSCI).
449. Wang, K., …, Tian, M. Z. (2021). The Construction and Analysis of ceRNA Network and Patterns of Immune Infiltration based on tumor mutation load in cervical cancer.
450. Bai, Y. X., Härdle, W. K., Pan, J. X., Rui, R. X., Tian, M. Z., Wang, K. and Zhang, X. L. (2021). Variable Selection for High Dimensional Additive Quantile Regression with Interactions under Marginality Principle. No. BIOMTRKA-21-344, under review, (SCI).
451. Rui, R. X. and Tian, M. Z. (2021). Non-iterative Gaussianization. Journal of Computational and Graphical Studies, No. GCGS-21-188, under review, (SCI).
452. Mei, B. and Tian, M. Z. (2021). The Unconditional Tilting Quantile Curve for Functional Data and Its Applications. Journal of Applied Statistics and Management, 18-0282, 2th revised, (CSSCI, CSCD).
453. Qian, M. L., Tian, X. T., Bai, Y. X. and Tian, M. Z. (2021). Hypothesis Testing for High-dimensional Covariance Matrices under Non-normality. Journal of Statistical Planning and Inference, … (SCI).
454. Gao, C. J., Wang, Y. D., Wang, L. and Tian, M. Z. (2021). Study on the comprehensive effect of multiple air pollutants on the incidence of pulmonary tuberculosis in Hotan, Xinjiang from 2015 to 2018, under review, –, (CSSCI, CSCD).
455. Kurbanyaz, G, and Tian, M.Z. (2021). A Novel Least Square Estimation for The Mixed Geographically Weighted Regression Models, Journal of Systems Science and Mathematical Sciences, (): –, under review, (CSCD).
456. Ma, S. P., Yu, K. M., Tang, M. L. and Tian, M. Z. (2021). Spatially correlated analysis of COVID-19 cases based on Bayesian functional models. Journal of the Royal Statistical Society: Series C. JRSSC-Sep-2021-0241, under review, (SCI, SSCI, Q1).
457. Hu, Y. N., Qi, J., Guo, S. H.,Tian, M. Z. (2021). Financial Network and Banking Systemic Risk Contagion. Operations Research and Management Science, A2021-1996, under review, (CSSCI, CSCD).
458. Luan, Z. M., Wang, K. and Tian, M. Z. (2021). Impact factors of critically ill patients with COVID-19 being transferred out of intensive care units based on the generalized linear mixed effects model. under review, (CSSCI).
459. Wang, K. and Tian, M. Z. (2021). Investigation on spatial variability of drinking water iodine and its influencing factors in Xinjiang, China. 6f11084d-8c5e-4ceb-8d43-538da90e16f4, BMC Public Health, under review, (SCI).
460. Xiong, W., Chen, Y. X., Härdle, W. K., Tang, M. L. and Tian, M. Z. (2021). Controlled Variable Screening via New Quantile Partial Measures under Tail-dependence Structure. The Annals of Statistics. ( ): un der review, (SCI, Q1).
461. Zhang, Y. X., Li, E. Q., Tang, M. L., Yu, K. M. and Tian, M. Z. (2021). Bayesian Latent Factor Analysis for Inference on Quantile Regression. Biometrics, BIOM2021705M, under review, (CSSCI).
462. Tian, Y. Z., Tian, F. M., Wang, Y. P. and Tian, M. Z. (2021). Bayesian Joint Quantile Regression Modeling of Multi-response Longitudinal Mixed Effects Models and An Application to Primary Biliary Cirrhosis Sequential Cohort Study. Statistics in Medicine, SIM-21-0999, (SCI).
463. Rui, R. X., Bai, Y. X. and Tian, M. Z. (2021). High dimensional Tensor Single Index Model. Journal of Machine Learning Research. No. 21-1381, (SCI, Q1).
464. Kurbanyaz, G, and Tian, M.Z. (2021). Generalized Method of Moments Estimation of Semi-parametric Spatially Varying Coefficient Error Autocorrelation Regression Model. SCIENCE CHINA Mathematics, No. SSM-2022-0004, under review, (SCI).
465. Hou, J. and Tian, M. Z. (2021). A Saddle Point Approximation Method for Unknown Population Distribution. Journal of Systems Science and Mathematical Sciences, No. , under review, (CSCD).
466. Bahani, M., Haritebieke, S, Nie, Y. W., Tian, M. Z. and Zhang, L. P. (2022). Comparison of Seasonal Epidemic Characteristics and Stage Trend of Pulmonary Tuberculosis in Xinjiang, 2005-2021. Practical Preventive Medicine, 29 (11), 1285-1289, (CA, JST).
467. Meng, L. J., Kurbanyaz, G. and Tian, M. Z. (2021). Analysis of the Impact of Macro Factors on COVID-19 in Chin. Journal of Shanxi University (Natural Science Edition), under review, (CSSCI).
468. Tai, L. N., Tao, L., Pan, J. X., Tang, M. L., Yu, K. M., Härdle, W. K and Tian, M. Z. (2023). Fully nonparametric inverse probability weighting estimation with nonignorable missing data and its extension to missing quantile regression, The Annals of Applied Statistics. No. AOAS2301-015, (SCI).
469. Bai, Y. X. and Tian, M. Z. (2022). Variable selection for censored grouped heterogeneous mixture Model. Working paper, –, (SCI).
470. Meng, L. J., Kurbanyaz, G. and Tian, M. Z. (2022). Analysis on Influencing Factors of China's carbon emission based on spatiotemporal variable coefficient autocorrelation model. Statistics and Decision, No. …1, under review, (CSSCI).
471. Tian, Y. Z. Tang, M. L., Mian, Z. B. and Tian, M. Z. (2022). Bayesian Quantile Regression Approach for Multi-response Longitudinal Mixed Effects Models: An Application To Primary Biliary Cirrhosis Sequential Cohort Study. Statistical Methods & Applications, ID: SMAP-D-22-00230, under review, (SCI).
472. Li, E. Q. and Tian, M. Z. (2022). Sure Independence Screening for Ultra-high Dimensional Competing Risks Mode. Statistics and Decision, No. , under revie, (CSSCI).
473. Zhang, Y. X. and Tian, M. Z. (2022). The Improvement of the Optimal Bonus-Malus Systems for Automobile Insurance. Statistics & Decision, No. , under review, (CSSCI).
474. Rui, R. X., Härdle, W. K. and Tian, M. Z. (2022). On Functional Partial Least Squares for Functional Linear Models. Journal of the American Statistical Association. ( ): Under review, (SCI, Q1).
475. Rui, R. X., Liu, Y. X., Wang, Z. H., Zhang, X. L., Wang, K., Zhang, L. P., Tang, M. L. and Tian, M. Z. (2022). Will the Re-emerging Monkeypox Become a Pandemic? A Spatiotemporal Trend Analysis. The Lancet of Infectious Diseases. Under review, (SCI, Q1).
476. Chen, X. D., Lu, D. M., Zhang, X. L., Tian, M. Z., Wang, K., Zhang, L. P. and Zheng, Y. L. (2022). Research on Health Management Guidance of Pulmonary Tuberculosis Patients in the Post Epidemic Era Based on Meta-analysis. Journal of Xinjiang Medical University. Under review, (CSTPCD).
477. Zeng, T., Ji, W. D., Lai, M., Li, Y., Tian, M. Z., Peng, Z. H. and Wang, K. (2022). Age-Period-Cohort analysis on the time trend of tuberculosis incidence in Jiangsu, China during 2009-2018, Tropical Medicine and Infectious Disease, No. , under review, (SCI). (IF:)
478. Guo, J. X. and Tian, M. Z. (2022). Quantile Regression with Semiparametric Non-random Missing Mechanism Based on Smoothed Empirical Likelihood, SCIENCE CHINA Mathematics, SSM-2022-0191, (SCI).
479. Guo, J. X. and Tian, M. Z. (2022). Quantile Regression with Semiparametric Non-random Missing Mechanism Based on Smoothed Empirical Likelihood. Sci Sin Math, SSM-2022-0191, under review, (Q1, SCI).
480. Guo, J. X. and Tian, M. Z. (2022). Smoothed Quantile Regression and SIR Algorithm with Nonignorable Nonresponse. Acta Mathematicae Applicatae Sinica, … (02):14-?, (CSCD).
481. Chen, H. L., Hu, X. X. and Tian, M. Z. (2023). Research on local linear embedding clustering algorithm for functional data. Journal of Applied Statistics and Management, Under review.
482. Liu, Y. and Tian, M. Z. (2022). Price Prediction of Electric Vehicle Based on Multi-logistic Model of Lasso Algorithm. Journal of Mathematics in Practice and Theory, No. , (CSSCI, CSCD).
483. Ma, S. P., Wei, C. H. and Tian, M. Z. (2023). Regression analysis for multilevel spatially dependent functions, Statistical Research, … (02):14-?, (CSSCI). Kurbanyaz, G., Ma, C. F. and Tian, M. Z. (2022). Orthogonality-projection-based Estimation for Mixed GWR Models with Heteroscedastic Errors. The Annals of Regional Science, No. ARSC-D-22-00136, (SCI).
484. Kurbanyaz, G., Ma, C. F. and Tian, M. Z. (2022). Orthogonality-projection-based Estimation for Mixed GWR Models with Heteroscedastic Errors. The Annals of Regional Science, No. ARSC-D-22-00136, (SCI).
485. Liang, J. W. and Tian, M. Z. (2023). Sequential Thresholded Quantile Estimator for Sparse Regression. Journal of the Korean Statistical Society, under review, (SCI).
486. Li, Y., Chen, H. L. and Tian, M. Z. (2023). A Study on the Spatial Effect of Environmental Regulation on Industrial Ecological Efficiency -A Test Based on China's Inter Provincial Panel Data, under review, (CSSCI).
487. Xiong, W., Yang, H. X. and Tian, M. Z. (2021). Clustering Social Factor Scaled Latent Space Models for Social Networks. Journal of Multivariate Analysis, (SCI).
488. Wang, W. X., Zhang, J. J. and Tian, M. Z. (2023). Variational Bayesian Variable Selection in Logistic Regression Based on Spik-and-slab Lasso. Journal of Applied Statistics and Management, , –, (CSSCI, CSCD).
489. Wang, Z. H., Ma, S. P., Rui, R. X. and Tian, M. Z. (2023). Sparse Smoothed Quantile Estimation for Partially Linear Functional Additive Models in high dimension, Statistica Sinica, SS-2023-0206.
490. Wang, W. X., Zhang, J. J. and Tian, M. Z. (2023). Variational Bayesian Regularization Quantile Regression. Applied Mathematics-A Journal of Chinese Universities, , –, (CSCD).
491. Guo, J. X. and Tian, M. Z. (2023).Semiparametric Bayesian quantile regression for non random missing data. Statistical Research, ? (5):?– ?. (CSSCI).
492. Hu, Y. N., Hou, T. T. and Tian, Z. M. (2023). Regional Differences, Dynamic Evolution and Policy-driven Mechanism of Gig Economy in China. Journal of Applied Statistics and Management, ? (6):?– ?. (CSSCI).
493. Zhang, Y. X., Tang, M. L., Yu, K. M., Härdle, W. K., Xu, L. W. and Tian, M. Z. (2023). The Kernel Trick of Latent Factor Model for Quantile Regression. Journal of the Royal Statistical Society: Series A. JRSSA-Aug-2023-0224, under review, (SCI, Q1).
494. Liu, S., Jiang, J. C., Hou, J., Wang, Z. H. and Tian, M. Z. (2023). Ultra-High Dimensional Additive Quantile Tensor Regression with Region Selection. Journal of the American Statistical Association. ( ): under review, (SCI, Q1).
495. Wang, W. X., Zhang, J. J. and Tian, M. Z. (2023). Asymmetric Horseshoe+ Prior for High Dimensional Quantile Regression with Variational Bayes. Mathematica Numerica Sinica.
496. Zeng, T., Lu, Y. Q., Zhao, Y. J., Guo, Z. H., Sun, S. Z., Teng, Z. D., Tian, M. Z., Wang, J., Li, S. L., Fan, X. C., Wang, W. M., Cai, Y. L, Liao, G. Z., Liang, X., He, D. H., Wang, K. and Zhao, S., (2023). Effectiveness of the booster dose of inactivated COVID-19 vaccine against Omicron BA.5 3 infection: A retrospective and matched cohort study of adult close contacts in Urumqi, China. The Lancet Regional Health - Western Pacific.
497. Kong, F. S., Wang, Z. H. and Tian, M. Z. (2023). Functional time-varying coefficient Cox model and its application. Statistical Research, 38 (?): ?-?, (CSSCI).
498. Liu, F. G., Gao, C. H., Tian, M. Z. (2023). Research on cognitive diagnosis of RRUM model in junior middle school mathematics teaching-Take a linear function as an example. Journal of Mathematics Education. (CSSCI).
499. Rui, R. X., Xiong, W., Pan, J. X. and Tian, M. Z. (2023). A Generalized Functional Linear Mixed Model with Application to a Schizophrenia Study, The Annals of Applied Statistics，ID AOAS2311-008, under review, (SCI)
500. Wang, W. X. and Tian, M. Z. (2023). Variational EM Algorithm for Quantile Regression in Linear Mixed Effects Models. Statistics in Medicine，under review, (SCI)
501. Hou, J., Liu, S. and Tian, M. Z. (2023). Research on Partial Linear Geographically Weighted Quantile Regression Model, Statistical Research, 3 (?): ?-?, under review, (CSSCI).
502. Kurbanyaz. G., Zhao, Z., Meng Li Jun, and Tian, M. Z. (2023). Profile Least Squares Estimation Method of Error Spatial Autocorrelation Geographically Weighted Regression Models, Acta Mathematicae Applicatae Sinica, ?4 (2), 1–24, under review, (CSCD).
503. Liu, Y. X., Wang, Z. H., Ma, Y. L., Zheng, Y., Yu, K. M. and Tian, M. Z. (2024). Estimation and Model Selection Procedures in Generalized Functional Partially Additive Hybrid Model with Diverging Number of Covariates. Journal of the Korean Statistical Society, JKSS-D-24-00068, under review, (SCI).
504. Hou, J., Liu, S. and Tian, M. Z. (2023). Relative Risk Confidence Interval Construction Based on Saddle Point Approximation under Poisson Distribution. Journal of Applied Statistics and Management, No., accept, (CSCD).
505. Xia, L. L., Lai, T. Y. and Tian, M. Z. (2024). Goodness-of-Fit Test for Functional Linear Model By the Modified Kernel-based Conditional Mean Dependence Measure. Acta Mathematica Sinica, English Series, No. AMSE-2024-0011, under review, (SCI).
506. Tian, Y. Z., Tang, M. L., Wong, C. and Tian, M. Z. (2024).Bayesian Analysis of Joint Quantile Regression for Multi-response Longitudinal Data with Application to Primary Biliary Cirrhosis Sequential Cohort Study. Statistical Methods in Medical Research, ? (1), ?–?, (SCI, Q1, IF = 3.2).
507. Zhou, M. Y., Mu, J. and Tian, M. Z. (2024). Measurement, Regional Difference and Convergence of Employment Scale in China's Service Industry Digital Economy, Statistical Research, 3 (?): ?-?, under review, (CSSCI).
508. Liang, J. W., Yu, K. M., Pan, J. X., Hardle, W. K. and Tian, M. Z. (2024). Identifying Interactions for Tensor Response Regression with Application to re-fMRI Data. Journal of the American Statistical Association, JASA-T&M-2024-0224, under review, (Q1, SCI).
509. Zhao, Z., Kurbanyaz. G., and Tian, M. Z. (2023). Confidence Interval Construction of the Difference between the Two Categories in multi-classification Outcome Measures based on the MOVER Method, Statistics and Decision, ?4 (2), 1–24, under review, (CSSCI).
510. Wang, Z. H., Yu, K. M., Tang, M. L., Härdle, W. K., Ma, S. P., Liu, Y. X., and Tian, M. Z. (2024). Partially Multivariate Functional Additive Convolution Smoothed Centile Regression. Journal of the American Statistical Association, JASA-T&M-2024-0106, under review, (Q1, SCI).
511. Zhou, Z. Y., Tian, M. Z. and Härdle, W. K., (2024). Nonparametric Conditional Graphical Model for Functional Data, Annals of Statistics, ID AOS2402-017, under review, (SCI).
512. Zhao, X. Y., Rong, Y. H. and Tian, M. Z. (2024). Garrotized kernel machine in semiparametric quantile regression, under review, (SCI).
513. Gu, Y. T., Yan, S. Z. and Tian, M. Z. (2024). A wind power prediction model based on dimension transformation: a case study of Xinjiang four Take wind farms. Journal of Xinjiang University (Natural Science Edition), 2024.02.25.0001 under review, RCCSE (A-).
514. Hu, Y. N., Qu, X. H. and Tian, M. Z. (2024). Spatial Autoregressive Quantile Models Based on Smoothed GMM and Its Application. Journal of Applied Statistics and Management, No., accept, (CSCD).
515. Zhang, L. P., Liu, F. G. and Tian, M. Z. (2024) Group regularization for zero-inflated geometric regression and its applications. Statistical Research, ? (5):?– ?. (CSSCI).
516. Niu, X. Y., Tian Y. Z., Tang, M. L., Tian, M, Z (2024). Multivariate contaminated normal mixture regression modeling of longitudinal data based on joint mean-covariance model. Statistical Analysis and Data Mining, 17(1), e11653. (SCI 25)
517. Tian, Y. Z., etc (2024). Bayesian Joint Relatively Quantile Regression Approach of Latent Ordinal Multi-response Linear Models. AStA Advances in Statistical Analysis, Submitted to the revision (SCI 29)
518. Sun, P. F., Zhuo, R. H. and Tian, M. Z. (2024). How Data Elements Drive Green Transformation of Enterprises? –– Evidence based on China's A-share listed companies Contemporary Finance & Economics, No. 2024.04.0318, (CSSCI).
519. Sun, P. F., Guo, Z. W. and Tian, M. Z. (2024). Will fintech affect a company's ESG performance? Statistics & Information Forum, No. 2024.04.0207, under review, (CSSCI).
520. Sun, P. F., Zhuo, R. H. and Tian, M. Z. (2024). The Impact of Data Elements on New Quality Productivity-Evidence based on China's A-share listed companies. Statistical Research, (5):?– ?. (CSSCI).
521. Sun, P. F., Zhang, Z. and Tian, M. Z. (2024). Concentration of Manufacturing Industries, Marketisation and New Quality Productivity. Statistics and Decision, No. zq2024.04.19.0004
522. Zhang, Q., Xiao, M. M., Liu, L. X. and Tian, M. Z. (2024). A Survey and Analysis of the Mental Health of College Students in the Post-Epidemic Era––Taking Yunnan Province Private Undergraduate Universities as an Example. Statistics and Decision, No. 2024.04.23.0005, under review, (CSSCI).
523. He, X., He, H., Tian, M. Z. (2024). Comparison of Confidence Interval Construction Methods for Relative Risk Under Binomial Distribution. Journal of Systems Science and Mathematical Sciences, No. 240328, under review, (CSCD).
524. Yang, L. P., Wang, C. X., Zhou, P., Xie, N., Tian, M. Z. and Wang, K. (2024). Seasonality, Trend, and Abrupt Change Detection for Time Series Analysis of the Brucellosis Reports in Xinjiang, China from 2010 to 2023. Scientific Reports, ID 22ce7bb3-5555-41f1-956c-f67460263dd6, under review, (IF 4.6, SCI, Q1).
525. Hao, X. Q., Zhang, L. P., and Tian, M. Z. (2024). Parameter Inference of Exponentiated Pareto Distribution under Generalized Progressive Hybrid Censoring Scheme. Under review.
526. Kong, F. S., Wang, Z. H., Liu, M. R. and Tian, M. Z. (2024). Partial functional variable coefficient smooth quantile regression based on LAMM algorithm. Under review. , Acta Mathematicae Applicatae Sinica, ?4 (2), 1–24, accept, (CSCD).
527. He, X., He, H., Zhang, L. and Tian, M. Z. (2024). Construction of Relative Risk Test Statistics Under Binomial Distribution. Chinese Journal of Applied Probability and Statistics. Under review, (CSCD).
528. Luo, Y. X., Zhao, K., Tian, M. Z. and Li, H. F. (2024). Mechanisms and Paths of Influence of Digital Transformation on Employment Quality under the Evolution of Labor Force Structure. Statistical Research, ? (5):?– ?. (CSSCI).
529. Hao, X. Q., Zhang, L. and Tian, M. Z. (2024). Parameter Inference of Exponentiated Pareto Distribution under Generalized Progressive Hybrid Censoring Scheme. Journal of Applied Statistics and Management, No., accept, (CSCD).
530. Li, Y., Tian, M. Z. and Chen, H. L.(2024). Research on the Impact Effect of Enterprise Digital Technology Innovation on New Quality Productivity. Under review, (CSSCI).
531. He, H., He, X., Zhang, L. and Tian, M. Z. (2024).Construction of Confidence Intervals for Relative Risk in Matched-Pair Design. Under review, (CSSCI).
532. Zhang, L. P. and Tian, M. Z. (2024). Zero-inflated Tests and Applications in Geometric Regression Modeling. Under review, (CSSCI).
533. Liu, S., Jiang, J. C., Hou, J., Wang, Z. H. and Tian, M. Z. (2024). Ultra-High Dimensional Additive Quantile Tensor Regression with Region Selection. Journal of the American Statistical Association，Manuscript ID JASA-T&M-2024-0490 , under review, (SCI, Q1).
2015
1) “Adaptive Quantile Regression and Its Applications to VaR” , The China-Japan Symposium. Invited speaker, Doshisha University, Japan, November 6-11, 2015.
2) The IMS-China International Conference on Statistics and Probability. Organizer of the Invited session IS70, University of Yunnan, Yunnan, China, July 1-4, 2015.
3) “Statistical Modeling of Complex Data and Its Applications”. A Series of Academic reports, Invited speaker, Lanzhou University of Finance and Economics, Lanzhou, Gansu, China, June 1, A. M., 2015.
4) “The Analysis of High Dimensional Data and Current Employment in China”. A Series of Academic reports, Invited speaker, Lanzhou University of Finance and Economics, Lanzhou, Gansu, China, June 1, P. M., 2015.
5) “Modeling of Complex Spatial-Temporal Data with Hierarchy”. The Establishment of the Branch of High Dimensional Data, Chinese Association for Applied Statistics (CAAS)and The 1st Symposium, Invited speaker, Anhui Normal University, Wuhu, Anhui, China, April 24-26, 2015.
6) The 9th National Symposium of on Survival Analysis and Applied Statistics. Secretary General and Organizer, Jilin University, Jilin, China, April 9-11, 2015. 2014
7) “Adaptive Quantile Regression with Precise Risk Bounds”. The enlarged Conference of The Chinese Association for Applied Statistics (CAAS)and Symposium on Frontier in Statistics, Invited speaker, Beijing University of Technology, Beijing, China, December 19-21, 2014.
8) “Adaptive Quantile Regression with Precise Risk Bounds”. Academic report, Invited speaker, North China University of Technology, Beijing, China, December 11, 2014.
9) “Statistical Inverse Problems and Applications”. The 1th International Conference on Big Data & Applied Statistics. Organizer General, Renmin University of China, Beijing, China, November 28-30, 2014.
10) “Complex Data Analysis with High Dimensionality”. The 11th Symposium on Data Mining & Business Intelligence and The Symposium on Applied Statistics across The Taiwan Strait. Invited speaker, Fu Jen Catholic University, Taiwan, October 30-31, 2014.
11) “Theory and Methodology for the Modeling of Complex Hierarchical Spatial-Temporal Data”. The 10th Conference of National Probability & Statistics in China. Invited speaker, Shandong University, Ji Nan, China, October 17-21, 2014.
12) “Calculation of High Dimensional VaR in Financial Risk Management”. A Series of Academic reports, Invited speaker, Lanzhou University, Lanzhou, Gansu, China, September 18, 2014.
13) “Analysis of Complex Data with High Dimensionality: Statistical Theory, Methodology & Applications and Current Employment in China”. A Series of Academic reports, Invited speaker, Lanzhou University, Lanzhou, Gansu, China, September 17, 2014.
14) “Statistical Theory and Methodology for Epidemiological Risk Indices”. A Series of Academic report, Invited speaker, Lanzhou University, Lanzhou, Gansu, China, September 16, 2014.
15) “Statistical Analysis of High Dimensional Data with Hierarchical Strucutre”. A Series of Academic report, Invited speaker, Lanzhou University, Lanzhou, Gansu, China, September 15, 2014.
16) “Statistical Inverse Problems”. Academic report, Invited speaker, Gansu Agricultural University, Lanzhou, Gansu, China, September 4, 2014.
17) “Statistical Inverse Problems and Applications”. The 6th International Forum on Statistics, Renmin University of China. Plenary speaker, Renmin University of China, Beijing, China, May 24-25, 2014.
18) The 8th National Symposium of on Survival Analysis and Applied Statistics. Secretary General and Organizer, Jilin University, Jilin, China, March 27-30, 2014. 2013
19) “Adaptive Quantile Regression with Precise Non-asymptotic Risk Bounds”. The 9th International Chinese Statistical Association (ICSA) International Conference: Challenges of Statistical Methods for Interdisciplinary Research and Big Data. Invited speaker, Hong Kong Baptist University, Hong Kong, December 20-23, 2013.
20) Joint conference of 5th AISECT and 4th EARBC. Session Chair, Renmin University of China, Beijing, China, July 6-7, 2013.
21) “Saddlepoint Approximation and Its Applications to Contemporary Risk Management”, The International Exchange for Chinese-Italian Statisticians. Invited speaker, the Faculty of Economic, University of Florence, Italy, January 28-29, 2013. 2012
22) “Statistical Inverse Problems and Applications”. The 7th National Symposium on Survival Analysis and Applied Statistics. Invited speaker and sectional chair, Kunming, China, August 26, 2012.
23) “Statistical Inverse Problems and Applications”. The 4th Annual Statistical Conference of China. Invited speaker and sectional chair, Kunming, China, August 25-28, 2012.
24) “Saddlepoint Approximation to Value-at-Risk Based on Time-inhomogeneous Volatility Models”. The 5th International Forum on Statistics, Renmin University of China. Invited speaker, Renmin University of China, Beijing, China, July 13-15, 2012.
25) “Exact Interval Estimation for the Risk Difference under Inverse Sampling”. The 2th International Symposium on Biostatistics. Invited speaker and sectional chair, Renmin University of China,Beijing, China, July 7-9, 2012.
26) Symposium on Business Statistics & Economic Measurement and Ten Year Anniversary for the Department of business statistics and econometrics. Invited guest, The Peking University. Beijing, China, June 2-3, 2012.
27) Scholarly Communication Meeting for Statisticians in Beijing. Invited guest, Capital University of Economics and Business. Invited guest, Beijing, China, June 2, 2012. 2011
28) “Adaptive Quantile Regression”. The National Statistical Symposium of China. Invited speaker, Beijing, China, December 10-11, 2011.
29) “Robust Estimation in Inverse Problems via Quantile Coupling”. The International Conference on Applied Mathematics and Statistics. Invited speaker and sectional chair, Beijing, China, August 21-22, 2011.
30) “Composite Quantile Regression Based on Varying-coefficient Models with Heteroscedasticity”. Chinese Statistician Symposium in Dali Yunnan. Invited speaker, Dali, Yunnan, China, August 1-4, 2011.
31) “Adaptive Quantile Regression with Precise Non-asymptotic Risk Bounds”. The 3th IMS-China International Conference on Statistics and Probability. Invited speaker, Xi An, China, July 8th-11th , 2011.
32) “Oracle Inequality for Statistical Inverse Problems”. The 1th International Conference on Mathematical Statistics and Related Fields. Invited speaker and sectional chair, Renmin University of China, Beijing, China, July 4th-6th , 2011.
33) “On The Bootstrap Quantile-treatment-effect Test”. The 4th Annual International Symposium on the Evaluation of Clinical Trials Methodologies and applications. Invited speaker and sectional chair, Renmin University of China, Beijing, China, June 30th-July 3th, 2011. 2010
34) “Saddle Point Approximation and Volatility Estimation of Value-at-Risk Adaptive”. China Forum on Risk Management and Actuarial. Invited speaker and sectional chair, Renmin University of China, Beijing, China, November 19th-21th, 2010.
35) “Locally Adaptive Quantile Regression and Its Applications”. International workshop “Quantile Regression:Theory and Applications”. Humboldt-Universität zu Berlin, Germany, October 5th-10th, 2010.
36) “Confidence Intervals for the Risk Ratio under Inverse Sampling”. The 1th Joint Biostatistics Symposium. Invited speaker and sectional chair, Renmin University of China, Beijing, China, July 17th-18th, 2010.
37) “Locally Adaptive Quantile Regression and Its Applications”. The 4th International Forum on Statistics, Renmin University of China and 5th International Symposium on Frontier of Statistical Science. Invited speaker and sectional chair, Renmin University of China, Beijing, China, July 10-12, 2010.
38) “Statistical Inverse Problems”. International Conference on Statistical Analysis of Complex Data Schedules. Invited speaker and sectional chair, Yunnan University, Kunming, China, July 1-3, 2010.
39) “Saddle Point Approximation and Volatility Estimation of Value-at-Risk”. International Conference on Quantaties Methods in Business Applications, invited speaker, Guanghua School of Management Peking University Beijing China, June 15-16, 2010.
40) “Exponential Risk Bounds and Locally Adaptive Varying Bandwidth Selection for Conditional Quantile Regression”. The 1th China-Korea Symposium on Modern Statistical Theory and Its Applications. Invited speaker, Renmin University of China, Beijing, China, June 14-15, 2010. 2009
41) “Robust Estimation in Inverse Problem via Quantile Coupling”. Research seminar, invited speaker, Renmin University of China, Beijing, China, November 25, 2009. 2008
42) “Locally Varying Bandwidth Selection for Conditional Quantile Regression”. Research seminar, invited speaker, C.A.S.E., Humboldt University, Germany, July 10, 2008 2006
43) “Semiparametric Quantile Regression Models for Hierarchical Data”. The 2th International Statistic Forum, Renmin University of China, Beijing, China, June 10-11, 2006
44) “Confidence Interval for Epidemiologic Rate Based on Saddle-point Approximations Approach under Inverse Sampling”. Research seminar, invited speaker, Central China Normal University, Wuhan, China. April 17, 2006.
45) “On Hierarchical Nonparametric Quantile Regression”. Research seminar, invited speaker. The Chinese University of Hong Kong, Hong Kong, March 28, 2006. 2005 2004
46) “Longitudinal Study of the External Pressure Effects on Children`s Mathematical Achievements”. The American Educational Research Association Conference, speaker, San Diego, USA, April 12-16, 2004. 2003
47) “Quantile Models: Theory and Practical Guideline for Empirical Research in Education”. Research seminar, invited speaker, University of Alberta, Canada, May 1 - July 31, 2003. 2002
48) “A Generalized Variance-ratio Test for A Heteroskedastic Regression”. The Beijing-Tianjin Conference of Chinese Probability and Statistics, invited speaker, Renmin University of China, China, May 20, 2002.
49) “Quasi-residuals Method in Sliced Inverse Regression”. The 7th Conference of Chinese Probability and Statistics, speaker, Northeast Normal University, Changcun, Jilin, China, September 19-24, 2002. 2001
50) “Statistical Diagnostics for Heteroscedasticity and Outliers”. Research seminar, invited speaker, Academy of Mathematics and System Sciences, Chinese Academy of Sciences, China, July 25, 2001.
51) “Quasi-residual Diagnostic Theory and Methodology for Heteroscedastic Models”. The 6th Conference of Chinese Probability and Statistics, invited speaker, Beijing, China, Sept. 19-24, 2001.