中国人民大学统计学院导师教师师资介绍简介-田茂再

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田茂再职称：教授（数理统计方向），博士生导师

职务：http://stat.ruc.edu.cn/en/teacher_more.php?cid=89248&id=54

电子邮箱： mztian@ruc.edu.cn
工作经历
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30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15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100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
2008. 03 — 2008. 06香港浸会大学数学系访问
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
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

兼任职务
起始年月 — 截止年月、任职单位名称、职务
1)2018.01 — 至今全国统计科学研究计划项目评审专家
2)2017.09 — 至今中国现场统计研究会第十届理事会理事
3)2017.09 — 至今北京市社科联专家
4)2017.08 — 至今首批中国人民大学“杰出”青年
5)2017.08 — 至今国际生物统计学会中国分会 (IBS-China) 常务理事
6)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
7)2016.03 — 至今北京高校少数民族代表人士
8)2016.04 — 至今北京市哲学社会科学评奖专家
9)2016.03— 2019.02 新疆维吾尔自治区“天山”
10)2015.06 — 至今北京市科学技术委员会专家
11)2015.11 — 至今国家社科基金同行评议专家
12)2015.10 — 至今国家出版基金评审专家
13)2015.10 — 至今国家社科中华学术外译专家
14)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
15)2014.10 — 至今中国概率统计学会第十届理事会理事
16)2014.04 — 至今中国博士后科学基金会评审专家
17)2013.08 — 2017.07 国际生物统计学会中国分会 (IBS-China) 常务理事
18)2013.05 — 至今北京市自然科学基金评审专家
19)2013.03 — 2015.02 甘肃省“飞天”
20)2013.02 — 至今评审专家
21)2012.02 — 至今国家留学基金评审专家
22)2012.10 — 至今中国现场统计研究会生存分析分会秘书长
23)2011.03 — 至今全国教育科学规划学科组专家
24)2011.03 — 至今北京市哲学社会科学学科评审组成员
25)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
26)2011.02 — 至今教育部人文社科项目评审专家
27)2010.08 — 至今美国统计协会会员 (ID. 165873)
28)2010.01 — 2015.05 北京市科学技术委员会专家
29)2010.06 — 至今国际计量经济协会会员(ID. **)
30)2008.11 — 至今《统计学评论》(Statistics Review) 副主编
31)2008.11 — 至今《统计研究》(Statistics Research) 编委
32)2008.11 — 至今国家自然科学基金同行评议专家
33)2008.07 — 2010.10 德国洪堡大学，SFB 649 FELLOW, 中方首席科学家
34)2006.01 — 至今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
35)2006.03 — 至今教育部“留学回国人员科研启动基金”评审专家
36)2007.09 — 至今中国人民大学概率论与数理统计研究所副所长
37)2001.01 — 至今担任超过50 本国际国内杂志的审稿人

基金项目
近十年，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200多篇文章，著书10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.**）, 教育部哲学社会科学研究重大课题攻关项目(No. 15JZD015 )等。
学术奖励
2006年以后获奖情况
2006年
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/t**_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）
2017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

开设课程
Publications
Books
Wu, X. Z. and Tian, M. Z. (2003), Diagnostics for Modern Regression Models. China Statistical Press. (In Chinese)
Tian, M. Z. (2011), Discovery and Innovation. Page 48–50, China Statistical Press. (In Chinese)
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)
Tian, M. Z. (2014). Theory, Methodology and Applications for Complex Data Statistical Inference, Science Press. (In Chinese)
Tian, M. Z. (2015). Quantile Regression & Complex Hierarchical Data Analysis，China Intellectual Property Publishing House.
Tian, M. Z. (2015). Advanced Theory for Hierarchical Quantile Modeling, Science Press. (In Chinese)
Tian, M. Z. (2015). Model Hierarchical Quantile Regression–Theory, Methodology and Applications, Tsinghua University Press. (In Chinese)
Tian, M. Z. (2017), Multivariate Statistical Analysisi with R, China Renmin University Press.
Tian, M. Z. (2019). Bandwidth Selection and Its Applications in Modern Nonparametric Statistics, China Science Press. (In Chinese)
Tian, M. Z. (2019), Hierarchical Quantile Modeling Theory, Methodology,Techniques and Application, Springer-Verlag. (In English, under press).
Selected papers
?2019
1. Li, E. Q., Tian, M. Z. and Tang, M. L. (2019). Variable Selection in Competing Risks Models
Based on Quantile Regression. Statistics in Medicine, DOI: 10.1002/sim.8326, (SCI).
2.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).
3.Bai, Y. X., Qian, M. L. and Tian, M. Z. (2019). Joint Mean-covariance Random Effect Model
for Longitudinal Data. Biometrical Journal, No. bimj., accept, (SCI).
4.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).

5.Tian, Y. Z., Shen, S. L., Lu, G., Tang, M. L. and Tian, M. Z. (2019), Bayesian LASSO-
Relarized Quantile Regression for Linear Regression Models with Autoregressive Errors, Communications in Statistics-Simulation and Computation, 48 (3): 777 –796, (SCI).
6. 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).
7.Wu, Y. K., Hu, Y. N. and Tian, M. Z. (2019). Simultaneous Estimation of Multiple
Conditional Regression Quantiles, Acta Mathematicae Applicatae Sinica (English Series), (No. e15150), accept, (SCI)
8.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).
9.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).
10.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).
11.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).
12.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).
13.Zhang, R. X. and Tian, M. Z. (2019). Multvariate Outlier Detection Based on Tilting
Minimum Covariance Determinant Method, Journal of Applied Statistics and Management, http://kns.cnki.net/kcms/detail/11.2242.01.**.1503.001.html, (CSSCI, CSCD).
14.Tian, Y. Z., Wang, L. Y., Tang, M. L. and Tian, M. Z. (2019), 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/**.2018.** , online, (SCI).
15.Tian, Y. Z., Wang, L. Y. Tang, M. L., and Tian, M. Z. (2019), Weighted Composite Quantile
Regression for Longitudinal Mixed Effects Models with Application to AIDS Studies, Communications in Statistics - Simulation and Computation, https://doi.org/10.1080/**.2019.**, (SCI)
16.Xia, L. L. and Tian, M. Z. (2019). Penalty likelihood estimation for a class of constrained
generalized additive model with zero-inflated count data. Statistics and Decision, No. **, accept, (CSSCI).
17.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).
18.Dai, X. W., Yan, Z., Tian, M. Z. and Tang, M. L. (2019). Quantile Regression for General
Spatial Panel Data Models with Fixed Effects. Journal of Applied Statistics, https://doi.org/10.1080/**.2019.** , (SCI).
19.Dai, X. W., Jin, L. B., Tian, Y. Z., Tian, M. Z. and Tang, M. L. (2019). Quantile Regression
for Panel Data Models with Fixed Effects under Random Censoring. Communications in Statistics-Simulation and Computation, https://doi.org/10.1080/**.2019.**, (SCI).
20.Wu, Y. K., Tang, M. L. and Tian, M. Z. (2019). General Composite Quantile Regression:
Theory and Methods. Communications in Statistics – Theory and Methods,
https://doi.org/10.1080/**.2019.**, (SCI).
21.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).
22.Yan, M. B. and Tian, M. Z. (2019). A Elastic Net Method Based on Variable Selection Events.
Journal of Mathematics in Practice and Theory, 49 (12): 215– 226, (CSCD).
23.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).
24. Yang, L., Tao, L. and Tian, M. Z. (2019). Qunatile Regression Based on Multi-period DID
Method and Its Applications. Statistics & Decision, (.),–, to appear (CSSCI).
25.Tian, M. Z. and Mei, B. (2019).Tilting Quantile Regression Modeling of Functional Data and
Its Applications. Statistical Research, 36 (8), 114 –128, (CSSCI).
26.Tai, L. N., Qian, M. L. and Tian, M. Z. (2019).Sample Selection Parametric Quantile
Regression and Its Application in Distribution Decomposition of Wage, Statistical Research, http://kns.cnki.net/kcms/detail/11.1302.C.**.1819.002.html , 2018–1483 (CSSCI).
27.Tai, L. N., Tao, L. and Tian, M. Z. (2019). Innovation Ideas of Government Statistics Work
Based on Big Data Supply Chain. Statistics & Decision, (.),–, accept, (CSSCI).
28.Mei, B. and Tian, M. Z. (2019). The Unconditional Tilting Quantile Curve for Functional Data
and Its Applications. Journal of Applied Statistics and Management, 18-0282 , 2th revised, (CSSCI, CSCD).
29.Dai, X. W., Li, E. Q. and Tian, M.Z. (2019). Quantile Regression for Varying Coefficient
Spatial Error Models, Communications in Statistics – Theory and Methods, (No. LSTA-2018-1172), 2th revised (SSCI).
30. Tian, Y. Z., Wang, L.Y., Tang, M. L. and Tian, M. Z. (2019). Weighted Composite Quantitle
Regression for Longitudinal Mixed Models: a MCEM Approach. Communications in Statistics-Simulation and Computation, No.LSSP-2018-0739 ,
https://www.tandfonline.com/doi/full/10.1080/**.2019.** , online, (SCI).
31.Liang, J. W. and Tian, M. Z. (2019). Outlier Diagnosis and Estimation via Volume
Sampling in Big Data. Journal of Applied Statistics and Management, No. 18-0D57, to appear, (CSCD, CSSCI).
32. 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).
33.Tian, Y. Z., Wang, L. Y., Tang, M. L., Zang, Y. C. and Tian, M. Z. (2019), Likelihood-based
Quantitle Autoregressive Distributed Lag Models and Its Applications. Journal of Applied Statistics, (https://doi.org/10.1080/**.2019.** ), (SCI).
34. Liang, J. W. and Tian, M. Z. (2019). Sufficient Dimension Reduction Method based on
Maximin Effect for Heterogeneous Data. Journal of Systems Science and Mathematical Sciences, No. 18450, to appear, (CSSCI).
35. Tian, Y. Z., Wang, L. Y., Wu, X. Q. and Tian, M. Z. (2019). Gibbs Sampler Algorithm of
Bayesian Weighted Composite Quantile Regression. Chinese Journal of Applied Probability and Statistics, 35(2), 178–192, (CSCD).
36.Tao, L., Tai, L. N. and Tian, M. Z. (2019). Quantile Regression for Panel Data with Fixed
Effects and Comparative Research. Statistics and Decision, No. , to appear, (CSSCI).
37. Mu, J. and Tian, M. Z. (2019). Bayesian Hierarchical Regression Model with Multivariate
Laplace Distribution and Its Application. Journal of Applied Statistics and Management, No. 19–0170, accept, (CSSCI).
38. Chu, Z. J., Tai, L. N., Xiong, W., Guo, X. and Tian, M. Z. (2019). Nonparametric Inverse
Probability Weighting For Quantile Regression With Missing Covariates, Acta Mathematica Sinica, English Series, B**, under review, (SCI).
39.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).
40.Yan, M. B. and Tian, M. Z. (2019). Variable Significance Test after Selection under Various
Distributions and Its Application to CEPS Data. Journal of Systems Science and Mathematical Science, ( ): –, accept, (CSCD).
41. Yu, Z., Tian, M. Z., Wang, C. J. and Ju, T. T.(2019) .Hierarchical Shrinkage Models via Variational Bayes. Statistical Research, No.2019-1084, –, under review, (CSSCI).
42.Ma, S. P., Sun, Q. H, Wu, Y. X. and Tian, M. Z. (2019). Research on Tensor Sufficient Dimension Reduction Method and Its Application. Statistical Research, …, –, under review, (CSSCI).
43.Yan, M. B. and Tian, M. Z. (2019). Selection of High Dimensional Variables Based on
Randomized Adaptive Lasso. Statistical Research, No. 2019 –0265, under review, (CSSCI).
44. Qian, M. L., Tao, L., Li, E. Q. and Tian, M. Z. (2019). Hypothesis Testing for Identity of
High-dimensional Covariance Matrices. Statistics and Probability Letters, No. STAPRO-D-19-00601, accept, (SCI).
45.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).
46.Wang, Z. H, Tian, M. Z., Hou, Z. M. and Chen, X. K. (2018). Measuring Quantile Effects
Based on Partial Least Squares Path Model, Journal of Systems Science and Mathematical Science, N0.19114: –, to appear, (CSCD).
47.Bai, Y. X., Yan, M. B., Tian, M. Z. and Zhai, H.W. (2019). Evaluating the Quality of Multidimensional Statistical Data Based on the Bootstrap Method. Statistics & Decision, No. , to appear, (CSSCI).
2018
48.Tian, M. Z. (2018). Exact Exponential Risk Bounds for Conditional Quantile Regression.
China Sciencepaper, 13(5), 598–610. (CSCD, CA, AJ, CSA, etc.).
49.Li, E. Q., Mei, B. and Tian, M. Z. (2018). Feature Screening Based on Ultrahigh Dimensional
Competing Risks Models, Vol. 48(8): 1061–1086.
50.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).
51. 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 University Bulletin of Natural Sciences and Engineering Series B: Mathematics and Statistics, 47 (4), 1023 –1039, (SCI).
52. 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.
53.Bai, Y. X. and Tian, M. Z. (2018). Functional Analysis of Variance Based on Multiple
Comparison Test, Statistics & Decision, 10, 62–56, (CSSCI).
54. 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).
55.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).
56. 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).
57.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).
58.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).
59. 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).
60.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).
61. 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).
62. 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).
63. 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
64.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).
65.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).
66.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).
67.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).
68.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).
69.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).
70.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).
71.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).
72.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).
73.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).
74.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).
75.Ma, C. X., Tian, M. Z. and Pan, J. X. (2017). Semiparametric Hierarchical Model with
Heteroscedasticity. Statistics and Its Interface, 10, 413–424, (SCI)

76.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)
77.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).
78.Bai, Y. and Tian, M. Z. (2018). Comparison and Application of Several High Dimensional
Variable Selection Methods, Statistics & Decision, 22, 11–16, (CSSCI).
79.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), 713–744, (CSCD).
80.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).
81. 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).
82. 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).
83. 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).
84.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).
85.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).
86.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).
87.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).
88.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).

89.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).
90.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).
91.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).
92. 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).
93.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).
94. 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).
95.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
96.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).
97.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).

98.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.
99.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).
100.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).
101.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).
102.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).
103.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).
104.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).
105.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)
106.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).
107.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).
108.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).
109.Huang, Y. L., Zhu, Q. Q. and Tian, M. Z. (2016). Nonparametric Quantile Regression
with Censored Data. Journal of Biomathematics, 3, 387– 407, (CSCD).
110. 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).
111.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).
112. 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).
113.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).
114.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).
115. 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)
116. 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).
117. 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）.
118.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).
119. 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).
120.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.**, View Table of Contents: http://aip.scitation.org/toc/apc/1738/1, (CPCI-S, ISTP).

?2015
121. Tian, M. Z. (2015). Several Hot Topics in Current Research of Statistical Theory of Big Data.
Statistical Research, vol. 32 (5): 3–12, (CSSCI).
122. 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).
123.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).
124.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).
125.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).
126.Wang, Z. and Tian, M. Z. (2015). Semiparametric Mode Regression Based on Locally
Linear Additive Models. Statistical Review, Vol. 9, 124 –142.
127.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).
128.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).
129.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).
130.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).
131.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).
132.Meng, L. B. and Tian, M. Z. (2015). Saddlepoint Approximation to An Important Statistic
Advances in Mathematics. 44 (5): 789–799 . (CSCD, CBST).
133.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).
134.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).
135.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).
136.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).
137.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).
138. 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
139.Xiong, W. and Tian, M. Z. (2014). Application of Quantile Regression Techniques in
Linear Heteroscedastic Model. Statistics Review，8, 115–128, (CSSCI).
140.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).
141.Xiong, W. and Tian, M. Z. (2014). A Novel Robust And Efficient Tool for Detecting
Heteroscedasticity. Journal of Mathematics and Statistics, 10: 169–185.
142.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).
143.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)
144.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).
145.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.
146.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.
147.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).
148.Xiong, W. and Tian, M. Z. (2014). Robust Estimators of Scale Function. Journal of Systems
Science and Mathematical Sciences. 34, 703–717， (CSCD).
149.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).
150.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).
151.Tian, Y. Z., Zhu, Q. Q. and Tian, M. Z. (2014). Inference for Mixed Generalized Exponential
Distribution under Progressively Type-II Censored Samples. Journal of Applied Statistics. 41(3), 660–676 (SCI).
152.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.
153.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).
154.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).
155.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).
156.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.
157.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,
CSCD)

?2013
158.Chen, Y. L. and Tian, M. Z. (2013). Comparative Study of Methods on Longitudinal Data
Analysis. Statistics & Decision, 10， 23–26, (CSSCI).
159.Tian, Y. Z., Su, Y. N. and Tian, M. Z. (2013). Optimal Estimation of EXPAR model.
Statistics Review.7，148–156. (CSSCI).
160.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).
161.Guo, J., Tang, M. L. and Tian, M. Z. (2013). Variable selection in high-dimensional partially
linear additive models for composite quantile regression . Computational Statistics and Data Analysis. 65, 56–67. (SCI).
162.Su, Y. N. and Tian, M. Z. (2013). Rolling Quantile Regression Model and Applications.
Statistics Review. 7，124–135.
?2012
163.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.).
164.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).
165.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).
166.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).
167.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).
168.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).
169.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).
170.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, (CSSCI).
171.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).
172.Guo, J. and Tian, M. Z. (2012). New efficient and robust estimation in varying-coefficient
models with heteroscedasticity. Statistica Sinica, 22, 1075–1101，(SCI, SSCI)
173.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).
174.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)
175. Tian, M. Z., (2012) . The Sentiment of Teaching Methodology in One`s Lecturing Life .
University Teaching Quality Quarterly, 3: 44–46.
?2011
176.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).
177.Tian, M. Z. et al. (2011) Abstract of the International Statistics Forum of 2010. Statistics &
Information Forum. 26, 60–111.
178.Su, Y. N. and Tian, M. Z. (2011). Adaptive Local Linear Quantile Regression, Acta
Mathematicae Applicatae Sinica (English Series). 27, 509–516, (SCI) .
179.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).
180.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
181.Tian, M. Z., Chan, N. H. (2010). Saddle Point Approximation and Volatility Estimation of
Value-at-Risk, Statistica Sinica, 20, 1239—1256, (SCI, SSCI)
182.Luo, Y. X. and Tian, M. Z. (2010). Quantile regression for panel data and its simulation
study. Statistical Research. 27, (10): 81–87, (CSSCI).
183.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)
184.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).
185.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).
186.Chen, D. Q. and Tian, M. Z. (2010). A Comparison of Several Different Approaches in
Sliced Inverse Regression. 4, 8–10, Statistics & Decision, (CSSCI).
187.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).
188. 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
189.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)
190.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)
191.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).
192.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
193. 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).
194.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).
195.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)
196.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).
197. 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).
198.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).
199. 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).
200.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
201.Tian, M. Z. and Chen, G. M. (2006), Quantile-hierarchical models. Science in China Series
A: Mathematics, 36(10), 1103–1118. (In Chinese), (CSSCI).
202. Tian, M. Z. (2006), A quantile regression analysis of family background factor effects on
mathematical achievements, Journal of Data Science, 4, 461–478, (EI).
203. 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)
204.Tian, M. Z. (2006), Two stages inferences for a semi-parametric regression model. Acta
Mathematicate Applicate Sinica, 29， 601–608, (CSSCI).
?2005
205.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).
206. 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
207.Tian, M. Z. and Li, G. Y. (2004), Quasi-residuals method in sliced inverse regression,
Statistics and Probability Letters, 66, 205–211. (SCI)
?2003
208.Tian, M. Z. and He, C. Z. (2003), A generalized variance-ratio test for a Heteroskedastic
regression, Mathematics in Economics, 20, 52–61, (CSSCI).
?2002
209.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
210.Tian, M. Z. and Wu, X. Z. (2001), A quasi-residuals method, Advances in mathematics, 30,
182–184, (CSSCI).
211.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
212.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
213. 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).
214. Si, S. J., Pan, J. X. and Tian, M. Z. (2012). Robust Estimation for Joint Mean-Variance
Models. (under review)
215. Tian, M. Z., Zhang, H. P. (2012). Parametric Modeling for Complex Large-scale Genetic
Data Sets with Multiple Ordinal Traits, (Submitted), (SCI).
216.Tian, M. Z. (2012). Locally Adaptive Quantile Regression And Its Applications, Journal of
the American Statistical Association. (No. JASA-T10-045 ), Under revision. (SCI)
217. Han, J. L., Pan, J. X. and Tian, M. Z. (2012). Parameters estimation in nonlinear
reproductive dispersion mixed models. (Under revision：No. 10109).

218.Tian, M. and Haerdle, W. (2012). Locally varying bandwidth selection for conditional
quantile regression. (Under review).

219. Tian, M. Z. and Chen, G. (2010). A limit distribution for the maximum of weighted sums
of m-dependent random variables. (Under review).

220. Chu, Z. J., Xiong, W., Guo, X. and Tian, M. Z. (2016). A New Approach to Quantile
Regression With Missing Covariates, Hacettepe Journal of Mathematics and Statistics, HJMS-15-65, (SCI).
221. Feng, D. D. and Tian, M. Z. (2013). Nonparametric quantile regression with censored
data. (Under review)
222. Li, Q. and Tian, M. Z. (2013). Locally smoothing composite quantile regression based on
semiparametric models. (Under review)
223. Lv, S and Tian, M. Z. (2013). Generalized varying coefficient mean covariance regression
methods for longitudinal data. (Under review)
224. 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)
225. 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)
226. 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)
227. Xiong, W. and Tian, M.Z. (2014). Reweighted efficient estimation in varying coefficient
models (SCI)
228. 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)
229. Tian, Y. Z. and Tian, M. Z. (2014). Estimating Mixed Exponential Distributions under
Hybrid Censoring , Scandinavian Journal of Statistics. (SCI)
230. Li, E. Q. and Tian, M. Z. (2014). Hierarchical Spline Models for Conditional Quantiles and
the Air Quality Index of Beijing. (CSSCI).
231. Liang, X. L. and Tian, M. Z. (2014). The Estimation of Epidemiological Rate under Inverse
Sampling Estimation Based on Hierarchical Models, under review, (CSSCI).
232. 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).
233. 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).
234. Xiong, W. and Tian, M. Z. (2014). A New Robust Regression Method Based on Sparsity
Function, under review, (SCI).
235.Li, E.Q. and Tian, M. Z. (2014), Hierarchical Spline Models for Conditional Quantiles and
The Air Quality Index of Beijing, under review, (SCI).
236.Yang, Y. Q. and Tian, M. Z. (2014), Quantile Regression Based on Single Index
Models for Longitudinal Data, under review, (CSSCI).
237.Ma, C. T and Tian, M. Z. (2014), Nonlinear Mixed Effects Model of ROC and Its
Medical Applications, under Review, (CSSCI).
238.Tian, M. Z., Tang, M. L., and Chan, P. S. (2010). Saddlepoint approximations to
conditional probability integral in metal analysis. (Under review).

239.Tian, M. Z. (2010). A limit distribution for the generalized Erd?s-Kac Statistic. (Under
review)
240.Meng, L. B. and Tian, M. Z. (2015). Semi-parametric Nonlinear Mixed Effects Models
Based on Saddlepoint Approximation, (SCI).
241.Tian, M. Z. (2015). Several Hot Topics In Current Research of Statstical Theory of Big
Data Statistical Research, 2014–1617 , (CSSCI).
242.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)
243. Tian, Y. Z., Han, X. F. and Tian, M. Z. (2015). Estimating Mixed Exponential
Distributions under Hybrid Censoring , Statistical Methodology . (SCI)
244. 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).
245.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).
246.Yuan, M. and Tian, M. Z. (2015). State Space Mixed Model for Negative Binomial Responses.
Under review, (CSSCI).
247.Shi, P. X. and Tian, M. Z. (2015). Bayesian Inference for Dynamic Zero-inflated Poisson
Model. Under review, (CSSCI).
248.Meng, L. B. and Tian, M. Z. (2015). Confidence Intervals Construction for Odds Ratio under
Binomial Sampling Based on Saddlepoint Approximation. Under review, (CSSCI).
249.Yang, Y. Q., Yan, Z.,Tian, M. Z. and Pan, J. X. (2019). Variable Selection in Joint Modeling
for Longitudinal Multiple Outcomes. Biometrics, BIOM**M , (SCI).
250.Zhang, Y. L. and Tian, M. Z. (2016). Parameter Estimation of Zero-Inflated Poisson Model
Based on Probit Regression. Statistical Review.
251.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).
252. 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)
253.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).
254.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.
255.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，B**, (SCI).
256.Xiong, W., Tang, M. L. and Tian, M. Z. (2018). Weighted Quantile Regression
Estimators and Variable Selection Procedures for a Version of the Varying Coefficient Model. The Canadian Journal of Statistics, No. CJS-18-0136, (SCI).
257. 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).
258.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).
259. Gu, M. C. and Tian, M. Z. (2016). Periodic Spatial-Temporal Quantile Model with Varying
Coefficients, Computational Statistics, No. COST-D-17-00325, (SCI).
260. Yuan, B. and Tian, M. Z. (2016). Mixed Copula Based on Empirical Distribution and
Its Applications to Financial Risk Management , Statistical Research, (CSSCI).
261. Qian, M. L. and Tian, M. Z. (2016). Analysis on Influencing Factors of PM2.5 in
Beijing Based on Quantile Regression, Forcasting, (CSSCI).
262. Wang, S. and Tian, M. Z. (2016). A Non-linear Hierarchical Growth Curve Model for
Forecasting the Outstanding Claims Reserves, Economic Management Journal，(CSSCI).
263. Zhang, W. S. and Tian, M. Z. (2016). Statistical Analysis of the Survival Rule of Electrical
Vehicles, Statistics & Information Forum, , (CSSCI, RCCSE).
264. 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.
265.Yan, Z. and Tian, M. Z. (2016). A Novel Testing Tool for Heteroscedasticity Using
Double Kernel Approach. Test, SEIO-D-16-00138, (SCI).
266.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)
267. 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).
268. 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)
269. 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)
270. 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).
271. Sun, W. B., Wang, L. and Tian, M. Z. (2016). The Determinants of Resident Income
Based on Classification Trees. Economic Review, (CSSCI).
272. 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).
273. 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).
274.Mei, B. and Tian, M. Z. (2016). Tilting Quantiles for Functional Data Based on Sparse
Smoothing, Biometrika, No. BIOMTRKA-16-478, (SCI).
275.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).

276.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).
277.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).
278.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., under review (CSSCI).
279.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.B**), under review, (SCI).
280.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).
281.Xiong, W. and Tian, M. Z. (2014). Hybrid Weighted Quantile Regression, Journal of Applied
Statistics , No. CJAS-2017-0918, under review, (SCI).
282. Li, E. Q., Dai, X. W. and Tian, M. Z. (2016). Variable Selection Based on Ultrahigh
Dimensional Competing Risks Models. , (No.) , ( ).
283. Tian, M. Z. and Haerdle, W. (2017). Exponential Risk Bounds and Locally Adaptive Varying
Bandwidth Selection for Conditional Quantile Regression, Bernoulli Journal, BEJ1503–029, under review, (SCI).
284.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) .
285.Xia, L. L. and Tian, M. Z. (2018). Employee Turnover Forecast Based on Lasso-Logistic
Regression Model. Statistics & Information Forum, No. , -. under review, (CSSCI).
286.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).
287.Bai, Y. X., Qian, M. L. and Tian, M. Z. (2018). Variable selection in high-dimensional
partially linear additive quantile regression via Atan penalty. Biometrics, No. BIOM**M, under review, (SCI).
288. Wang, C. Y., Tian, M. Z. and Tang, M. L. (2018). Nonparametric Quantile Regression
with Missing Data Using Local Estimating Equations. Biometrika, No. , under review, (SCI).
289. Hou, Z. M., Tian, M. Z., Wang, Z. H and Dou, Y. (2018). Study on the impact of
technological innovation on the income gap between urban and rural residents—Based on the experience analysis of western national agglomeration area, No. –, under review, (CSSCI).
290.Tao, L., Tai, L. N. and Tian, M. Z. (2018). Quantile Regression for Panel Data with Fixed
Effects and Comparative Research. The Journal of Quantitative & Technical Economics, No. , under review, (CSSCI).
291.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).
292.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).
293. 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).
294. 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).
295.Cao, R. and Tian, M. Z. (2019). Study on Executive Compensation of Private Listed Companies Based on Unconditional Quantile Regression, Systems Engineering-Theory & Practice, No. , under review, (EI, CSCD).
296.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).
297.Rui, R. X. and Tian, M. Z. (2019). A Novel Quantile Test Based on Percentile Deviation. Chinese Annals of Mathematics, _A(2): – ，(CSCD, CSCI).
298.Hu, Y. N., Wang, J. T. and Tian, M. Z. (2019). Foreign Trade, Technological Progress and
Economic Growth: An Empirical Study Based on the Spatial Panel Simultaneous Equations. Statistical Research, No. , under review.
299.Tai, L. N., Tao, L. and Tian, M. Z. (2019). Bayesian Semiparametirc Quantile Sample
Selection Model with Heterogeneity, The Journal of Econometrics , (.),–, , (SCI).
.
300.Xiong, W., Wang, J. and Tian, M.Z. (2019). Robust Interpolation of Missing Data based on
Additive Model. Journal of Applied Statistics and Management, No. 2018.12.12.0001, (1): – , (CSCD).
301.Xiong, W., Wang, J. and Tian, M.Z. (2019).Robust System Risk Measurement in Financial Markets -The analysis of the Hang Seng Composite Index Based on CoVaR and MES. Journal of Applied Statistics and Management, No. 2017.05.08.0001, (1): – , (CSCD).
302.Tian, Y. Z., Wang, L. Y. and Tian, M. Z. (2019). Bayesian LASSO-Regularized Weighted Composite Quantile Regression With Its Application, Acta Mathematicae Applicatae Sinica (English Series), (No. …), under review, (SCI).
303.Zhang, R. X. and Tian, M. Z. (2019). Sliced Inverse Quantile-based Regression for
Dimension Reduction, Journal of…, , under review, (SCI).
304.Su, P. and Tian, M. Z. (2019). Censored Quantile Correlation Screening, Biometrics , No.
BIOM**M , under review, (SCI).
305.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).
306.Han, Z. K. and Tian, M. Z. (2019). Research on Fraud Detection Models in Third Party
Payment, Journal of…, , under review, (CSSCI).
307.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).
308.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).
309.Zhang, Y. X.and Tian, M. Z. (2019). Semiparametric Bayesian Hierarchical Quantile
Regression Model for Insurance Data, The Journal of , No., under review, (SSCI).
310.Yan, M. B. and Tian, M. Z. (2019). The Oracle Properties of Adaptive Lasso under Selective
Inference Scheme. Journal of…, , under review, (CSCD).
311.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).
312.Tian, Y. Z., Tang, M. L. and Chan, W. S. and Tian, M. Z., (2019). Bayesian Bridge-
Randomized Penalized Quantile Regression for Ordinal Longitudinal Data and the Analysis of Firm`s Debt Maturity Structure, No. , under review, (SCI).
313.Tao, L., Tai, L. N. and Tian, M. Z. (2019). Minimum Distance Estimator of Instrumental Variable Quantile Regression for Panel Data with Fixed Effects. Journal of Business & Economic Statistics, No. JBES-P-2019-0312, under review, (SSCI).
314.Tian, Y. Z., Tang, M. L., Chan, W. S. and Tian, M. Z. (2019), Bayesian Bridge-Randomized Penalized Quantile Regression for Ordinal Longitudinal Data and the Analysis of Firm`s Debt Maturity Structure. Statistical Papers, (No. …), under review, (SCI).
315.Wang, W. X. and Tian, M. Z. (2019). Bayesian Quantile Regression and Its Applications in Generalized Linear Mixed Effects Models, Statistics & Information Forum, No. 2019.07.0172, (CSSCI).
316.Zhang, C. L. and Tian, M. Z. (2019). Construction of Bootstrap Confidence Intervals Based on Bayes. Statistics and Decision, No. , under review, (CSSCI).
317.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).
318.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).
319. 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).
320.Liu, Y. and Tian, M. Z. (2019). Pricing of "Take Photos and Make Money" APP Task Based on Logistic Regression Model, Journal of Mathematics in Practice and Theory, No. 19-1694, under review, (CSCD).
321.Liu, Y. and Tian, M. Z. (2019). Economic Development
研究方向
Adaptive smoothing; Big data; Bayesian statistical inference; Computer intensive methods; Extremes and heavy tails; Functional data analysis; Financial econometrics and risk management; Hierarchical models; Hierarchical- quantile regression modeling; High dimension reduction; Inverse problems; Large sample theory; Large scale data analysis; Model selections; Nonparametric and semiparametric modeling; Order statistics; Quantile regression; Quantitative finance; Robust statistics; Saddlepoint approximations with applications; Spatial-Temporal modeling; Statistical diagnostics; Statistical methods in epidemiological risk; Stochastic simulations; Time series modeling; Volatility modelling; Big data; Spatial-Temporal Modeling,......
论文成果
（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)
（三）指导学生情况
该同志从教30余载，教过的学生人数过万，其中最近10年左右指导的博士生、研究生等情况如下：
PH.D STUDENTS SUPERVISED (17)
?2018
?Yanxia Liu (刘艳霞)：@qq.com
?Shaopei Ma (马少沛)：@qq.com
?2017
?Yongxin Bai (白永昕)：@qq.com
?Li Tao (陶丽)：**@163.com
?2016
?Lingna Tai (邰凌楠): int_eve@163.com
?Maobo Yan (闫懋博): ryustage@163.com
?2015
?Erqian Li (李二倩): li2qian@mail.ustc.edu.cn
?Bo Mei (梅波): meibo119@126.com
?2014
?Xiaowen Dai (戴晓文)：daixiaowendaisy@163.com
?Yanan Hu (胡亚南)：yananhu@139.com
?2013
?Yanke Wu (吴延科): yanke.wu@163.com
?Zhen Yan (晏振)：mathyanzhen@163.com
?2012
Jian Zhou (周健): zhoujianrss@ruc.edu.cn
Wei Xiong (熊巍)：xwhehe.26@163.com
?2011
Yuzhu Tian (田玉柱)：pole1999@163.com
?2010
Yunan Su (苏宇楠)：salinasu@163.com
?2009
Youxi Luo (罗幼喜)：youxiluo@163.com
POSTDOCTORAL FELLOWS SUPERVISED (3)
?2018
Yongxia Zhang (张永霞)：bingningyu@ruc.edu.cn
?2015
Liwen Xu (徐礼文)：xulw163@163.com
?2014
Zonghu Wang (王纵虎)：zonghuwang@petrochina.com.cn
MASTER STUDENTS SUPERVISED（95）
?2018
Jingxuan Guo (郭婧璇): jxguo1996@foxmail.com
Congyue Li (李聪玥): @qq.com
Rongxiang (芮荣祥)：raynerrui@qq.com
Yihao Wang (王一昊): @qq.com
Zhen Yu (虞祯): amy.yuzhen@foxmail.com
Mengyu Zhou (周梦雨) **@163.com
Yu Liu (刘娱) @qq.com
Chen Liang (梁辰) liangchen@bcicc.com
?2017
Rui Cao (曹睿): cronaldo@ruc.edu.cn
Liner Gao (高霖儿): @qq.com
Jincun Guo (郭锦纯): @qq.com
Zikun Han (韩梓坤): @ qq.com
Jinwen Liang (梁晋雯):liangjinwen@ruc.edu.cn
Xu Zhang (张旭): @qq.com
Juan Mu (慕娟): **@163.com
Chonglinag Zhang (张茺喨): @qq.com
Huan Zhang (张欢): zhangh33@126.com
Yang Liu (刘洋): **@126.com
Yanfei Sun (孙燕飞): syfcab@126.com
?2016
LingxinDang (党领欣): danglingxin@163.com
Tingting Li (李婷婷): **@qq.com
Yijian Liu (刘一鉴): muse726@163.com
Peng Su (苏鹏): @qq.com
Lan Yang (杨澜): yanglan14991@163.com
Ying Yu (余颖): @qq.com, yuying_ruc@163.com
Ruoxuan Zhang(张若璇): kdzrx@mail.ustc.edu.cn, rdzrx@ruc.edu.cn
Lili Xia (夏丽丽)： BJxialili@163.com
Weixian Wang (王维贤)： @qq.com
?2015
Xiaoshen He (何晓申)：skss309@163.com
Yarong Wang (王亚荣)：@qq.com
Yanfei Jia (贾燕飞)：@qq.com
Ye Liu (刘烨)：@qq.com
Manling Qian (钱曼玲): @qq.com
Li Tao (陶丽)：**@163.com
Chunyu Wang (王春雨): cywang0315@126.com
Zhang Taotao (张陶陶)：zhangtaotao604@163.com
Yuhan Zhou (周雨菡)：zhouyuhan_001@163.com
Dongmei Tian (田东梅): tiandongmei_1017@163.com
Tianjia Zhang (张田佳): tracy1023@foxmail.com
?2014
Meichuan Gu (谷梅川): gramce@163.com
Lei Li (李蕾): @qq.com
Shaoyang Li (李少洋): li.shaoyang.lsy@gmail.com li.shaoyang@yahoo.com
Xintao Tian (田鑫涛): xttian90@126.com
Shan Wang（王珊）： @qq.com
Bo Yuan (袁博)：yb1992yuanbo@163.com
Yuanjie Zhang (张元杰)：jianyouyan@163.com
Yongxin Bai (白永昕)：@qq.com
Mengya Hu (胡梦雅)：humengya@nssc.ac.cn
?2013
Erqian Li (李二倩): li2qian@mail.ustc.edu.cn
Jing Luo (罗静): luojing@qq.com
Puxin Shi (史普欣)：gonewday@163.com
Xiaohe Wang (王晓荷) wxh1234____@hotmail.com
Meng Yuan (袁梦)：@ruc.edu.cn
?2012
Xiaolin Liang (梁晓琳)：liangxiaolinlxl@163.com
Chuntao Ma (马春桃)：machuntao1990@126.com
Chuoxin Ma (马绰欣)：horse1141@163.com
Lingbin Meng (孟令宾)：menglb2011@sina.com ， victorymeng2012@163.com
Zhen Wang (王榛）：schumilk@hotmail.com
Yaqi Yang (杨亚琦)：yangyaqihappy@163.com
Yalli Zhang (张亚丽)：zhyli0504@126.com
?2011
Jing He (何静)：tongji**@163.com
Yanan Hu (胡亚南)：yananhu@139.com
Yali Huag (黄雅丽)：@qq.com
Qian Li (李茜)：lily29.lee@gmail.com , sukikazuya@126.com
Suqian Liu (刘甦倩): vivian890721@sina.com
Shuang Lv (吕爽)：**@163.com
Qianqian Zhu (朱倩倩)：zhunanapig@126.com , zhunanapig@aliyun.com
?2010
Zhaoji Chu (储昭霁)：zhaojichu@126.com
Dadao Feng (封达道)：fengdadao@gmail.com
Zhaoyuan Li (李兆媛)：lzyruc@gmail.com ，zyli12@hku.hk
Shijing Si (司世景)： sisijing2006@163.com
Wentao Xia (夏文涛)：xwt0410@163.com
Wei Xiong (熊巍)：xwhehe.26@163.com
?2009
Liang Yan (陈彦靓)：couragecyl@163.com
Jie Guo (郭洁)：**@bjtu.edu.cn
Yanfei Kang (康雁飞)：yanfei.kang@monash.edu， feizai060@sina.com
Yaohua Rong (荣耀华)： rongyaohua163@163.com
Wei Wang (王伟)： fjxpwangwei@163.com
?2008
Shujing An(安姝静)：jingjbaobao@126.com, jingjbaobao@126.com
Boyu Chen(陈博钰)：happy.cby@ruc.edu.cn ，happy.cby@163.com
Bowen Fan(范博文)：nekoferry@yahoo.com.cn
Yan Fan (范燕)：fan-yan1985@163.com
Chunbo Jiang (姜春波)：jcb325@163.com
Weihua Ma(马维华)：maweihua168@sina.com
Yunan Su(苏宇楠)：salinasu@163.com
Yuanyuan Zhang (张圆圆)：apple**@126.com
?2007
Jieyu Fan (范洁瑜)：yuyu_fan@126.com , yuyufan05@gmail.com
Ning Zhang (张宁)：ningzhang198412@163.com ，jacosin@163.com
Cheng Dai (戴成)：daicheng@ruc.edu.cn
Zhenchao Qian (钱政超)：ciciyy111.student@sina.com
Hengze Shi (石恒泽)：stone_hengze@yahoo.com.cn
Jian Zhou (周健): zhoujianrss@ruc.edu.cn
?2006
Pengpeng Zhou (周朋朋)：peng.zhou@ruc.edu.cn , chowpengpeng@gmail.com
?2005
Yuan Li (李远): i222@ruc.edu.cn
UNDERGRADUATE THESES SUPERVISED (47)
?2004
Chuanneng Huan (黄传能)：cnhuang_2008@163.com
Tian Chen (陈甜)：trollycn@gmail.com
Mengque Liu (刘蒙阕): lmqchristina@hotmail.com
Rui Pan (潘蕊): panrui.ioio@gmail.com
Huan Wang (王欢)： huanhuan1985@yahoo.cn
Ke Wen (文科): liudehuaiou@sina.com
?2005
Hao Bo (薄皓): thomas.halcyon@gmail.com
Han Chen (陈涵) hanaa@163.com
Jian Wang (王剑): wangjian0516@gmail.com
Wei Wang (王伟)：fjxpwangwei@163.com
?2006
Zhong Gao (高仲): gaozhong4858@hotmail.com
Lanfeng Pan (潘岚锋)：panlanfeng@gmail.com
?2007
Qi An (安琪)：anqier89@126.com
Jing Chen (陈静)：fionafun@126.com
Lu Li (李璐)： xxlunaxx@qq.com
Chengcheng Liu ( 刘程程)：yatoucheng@w.cn , Chengcheng.Liu@sc.com
Cong Shen (沈聪)：shencongpearl@126.com
?2008
NULL
?2009
Sai Li (李赛): saili.forward@gmail.com
Xuecong Jia (贾雪骢): jiaxuecong@163.com
Shilun Qu ( 曲施伦)：ai4inmortal@sina.com
Chenyang Zhang (张晨阳): zhangcy0114@163.com
Shinan Zhou(周诗楠): zhoushinan52@163.com
?2010
Shiruo Cao (曹诗若)：caoshiruo1234@163.com
Minjia Chen(陈岷佳) minjia2010@ruc.edu.cn
Zhouyang Linghu (令狐洲洋): linghuzhouyang@ruc.edu.cn
Mengxi Wang (王梦溪): dlovenforever@hotmail.com
JingWu (武竞): ruc_jingwu@163.com
Qile Yang (杨其乐): larry0317@gmail.com
?2011
Zhangzhi Cao (曹彰之): caozhangzhi@ruc.edu.cn
Jie Song (宋洁): jone_song@163.com; @qq.com
Jia Wang (王佳): wangjia_1993@163.com
Shuang Wang (王爽): **@163.com
Taotao Zhang (张陶陶): zhangtaotao604@163.com
?2012
Yue Bai (白玥): baiyue@ruc.edu.cn
Yuan Mei (梅园): @qq.com
Wensha Zhang (张文莎): @qq.com
?2013
Yuanfang Qiao(乔媛芳): @qq.com
Yongxin Shuai (帅咏昕): shuai.yongxin@163.com
Ke Wang (王可): @qq.com
Lan Wang (王岚): @ruc.edu.cn
Chenling Yang (杨晨泠): annabelyang@qq.com
Qi Zheng (郑琪): preciousnereus@163.com
?2014
Yuqing Lu (芦雨晴): **@163.com
Yurong Wang (王宇榕): muliwyr@163.com
?2015
Yuxuan Li(李宇轩): lyx@ruc.edu.cn
Yuting Qin (秦宇婷): **@163.com
Huilin Zhang(张慧琳): @ruc.edu.cn
VISITING SCHOLARS SUPERVISED (5)
?2018
Ming Xie (解铭) nalanyu1984@126.com
?2016
Jing Guo (郭晶)：@qq.com
?2014
Chahua Ye (叶茶花)：@qq.com
?2011
Yanping Ran (冉延平)：yanpingran@sina.com
?2009
Junlin Han (韩俊林)：hanjunlin001@vip.163.com

著作成果
Tian, M. Z. (2014). Theory, Methodology and Applications for Complex Data Statistical Inference, Science Press. (In Chinese)
Tian, M. Z. (2015). Quantile Regression & Complex Hierarchical Data Analysis，China Intellectual Property Publishing House.
Wu, X. Z. and Tian, M. Z. (2003), Diagnostics for Modern Regression Models. China Statistical Press. (In Chinese)
Tian, M. Z. (2011), Discovery and Innovation. Page 48–50, China Statistical Press. (In Chinese)
Tian, M. Z. (2019). Bandwidth Selection and Its Applications in Modern Nonparametric Statistics, China Science Press. (In Chinese)
Tian, M. Z. (2015). Advanced Theory for Hierarchical Quantile Modeling, Science Press. (In Chinese)
Tian, M. Z. (2015). Model Hierarchical Quantile Regression–Theory, Methodology and Applications, Tsinghua University Press. (In Chinese)
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)
Tian, M. Z. (2016), Hierarchical Quantile Modeling Theory, Methodology,Techniques and Application, Springer-Verlag. (In English, under press).
Tian, M. Z. (2017), Multivariate Statistical Analysisi with R, China Renmin University Press.
会议论文
?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. Website: http://www.2015imschina.com
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-Universit?t 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.

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