Education

B. S. (1991), National University of Defense Technology, China

(1993), Hunan Institute of Education, China

M. A. (1998), University of Hunan, China

Ph. D. (2001), University of Nan Kai, China

Current research interests

Quantile regression; Hierarchical models; Hierarchical- quantile regression modeling; Big data modeling; Adaptive smoothing; Bayesian statistical inference; Computer intensive methods; Extremes and heavy tails; Functional data analysis; Financial econometrics and risk management; High dimension reduction; Inverse problems; Large sample theory; Large scale data analysis; Model selections; Nonparametric and semiparametric modeling; Order statistics; Quantitative finance; Robust statistics; Saddle point approximations with applications; Spatial-Temporal modeling; Statistical diagnostics; Statistical methods in epidemiological risk; Stochastic simulations; Time series modeling; Volatility modelling,......

Scientific experience

2017.01—2017.03,Columbia University, USA

2015.11—2015.11,Doshisha University, Japan

2015.09—2015.10,Rhodes, Greece

2013.03—present,Flying Apsaras Scholar of Ganzu Province

2012.12—2013.01, Visiting Scholar of the Faculty of Economic, University of Florence, Italy.

2012.10—2012.11, Visiting Scholar of Tokyo University, Japan

2012.08—2012.09, Visiting Scholar of Manchester University, University of Brunel, United Kingdom.

2011.12—2012.03, Visiting Scholar of Yale University, United States of America.

2011.07, Visiting Scholar of the Chinese University of Hong Kong, Hong Kong.

2010.10.5—10 SFB fellow, Humboldt University，Germany

2009.12—2010.1 SFB fellow, Humboldt University，Germany

2008.10—2009.11, Research Fellow, University of Melbourne, Australia

2008.07—2009. 01, SFB fellow, Humboldt University, Germany

2008.03—2008.06, Visiting Research Scholar of Baptist University of Hong Kong, Hong Kong.

2007.08—2007. 11, Visiting Research Scholar of Baptist University of Hong Kong, Hong Kong.

2005.07—2007.2, Postdoctoral fellow, the Chinese University of Hong Kong and the Baptist University of Hong Kong, Hong Kong.

2004.11—2005.02, Associate researcher, the Chinese University of Hong Kong, Hong Kong.

2004.01—07, Postdoctoral fellow, Department of Mathematics and Statistics, University of Calgary, Canada.

2002.01—2003.12, Postdoctoral fellow, Canadian Center for Advanced Studies of National Databases, University of Alberta, Canada.

2002.08—2002.11, Assistant Researcher, Chinese University of Hong Kong, Hong Kong.

2001.06—2004.08, Postdoctoral fellow, Academy of Mathematics and System Sciences, Chinese Academy of Sciences, China.

Publications

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), AdvancedStatistical Modeling in Medicine, Elsevier, under review.

Selected papers

2024

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).

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).

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, 33 (7), 1163–114, https://doi.org/10.1177/09622802241247725 , (SCI, Q1,IF = 3.2).

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).

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, 54: 1–32, doi: 10.1360/SCM-2023-0633，(SCI, Q1)

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).

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, 68, 691–700, DOI：https://doi.org/10.1007/s00484-023-02615-z , (IF 3.6, SCI, Q2).

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.

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).

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).

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).

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).

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).

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).

Kurbanyaz, G. and Tian, M.Z. (2024). Confidence Intervals Construction for Relative Difference under Binomial Sampling based on MOVER Method. Journal of Systems Science and Mathematical Sciences, 44 (10), 3095–3114, (CSCD).

Tian, Y. Z., Wu, C. H., Tang, M. L. and Tian, M. Z. (2024). Bayesian Relative Composite Quantile Regression with Ordinal Longitudinal Data and Some Case Studies, Journal of Statistical Computation and Simulation, https://doi.org/10.1080/00949655.2024.2335399 , (SCI).

Li, Y., Chen, H. L. and Tian, M. Z. (2024).Statistical measurement and spatiotemporal evolution characteristics of the development level of new quality productive forces. Statistics and Decision, 40 (09): 11-17, (CSSCI).

Tian, Y. Z., Wu, C. H., Tai, L. N., Mian, Z. B. 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/10.1002/sam.11683,(SCI).

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).

Niu, X. Y., Tian, Y. Z.,Tang, M. L. and 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, https://doi.org/10.1002/sam.11653, (SCI).

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, accept, (SCI).

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).

Kurbanyaz, G., Zhao, Z., Meng, L. J., Ma, Y. L. and Tian, M. Z. (2024). Profile Least Squares Estimation of Error Spatial Autocorrelation GWR Models, Acta Mathematicae Applicatae Sinica, 47 (5), 739–769, (CSCD).

Zhang, Y. X., Li, E. Q., Tang, M. L., Yu, K. M. and Tian, M. Z. (2024). Bayesian Latent Factor Analysis for Inference on Quantile Regression. Journal of Applied Statistics,237913259.R1, under review, (SCI).

Tian, Y. Z., Wu, C. H., Tang, M. L. and Tian, M. Z. (2024). Bayesian Joint Relatively Quantile Regression of Latent Ordinal Multivariate Linear Models with Application to Multirater Agreement Analysis. AStA Advances in Statistical Analysis, 1-32, https://doi.org/10.1007/s10182-024-00509-y, (SCI).

Hao, X. Q., Zhang, L. and Tian, M. Z. (2024). Parameter Inference of Pareto Distribution under Generalized Progressive Hybrid Censoring Scheme. Journal of Harbin University of Commerce(Natural Sciences Edition), No.24-01D0, (ICI).

Liu, F. G., Chen, Z. R., Xu, J., Zheng, Y. Y., Su, W. Y., Tian, M. Z. and Li, G. (2024).Interpretable machine learning-based influence factor identification for 3D printing process structure linkages. Polymers, 16, x. https://doi.org/10.3390/xxxxx, (SCI, IF:4.1/Q1).

Liang, J. W., Tian, M. Z. ang Rong, Y. H. (2024).Nonparametric Maximin Aggregation for Data with Inhomogeneity. Communications in Statistics - Theory and Methods, DOI:10.1080/03610926.2023.2279913, accept, (SCI).

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 Wuhan University of Technology（Information & Management Engineering）No. 2024-00216, accept.

2023

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)

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).

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

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).

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)

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).

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).

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).

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).

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).

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).

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).

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).

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).

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.

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).

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).

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).

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/

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).

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.

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)

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).

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).

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).

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).

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).

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).

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).

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).

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).

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).

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).

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).

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)

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).

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, ().

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

Tian, Y. Z., Tian, M. Z. and 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.

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).

2022

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-relatedDisorder, Journal of the Royal Statistical Society, 185 (2), 644–667, https://doi.org/10.1111/rssa.12963 , (SCI, SSCI, Q1).

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).

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).

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).

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).

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).

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).

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).

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).

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).

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)

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)

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)

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).

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).

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)

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).

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).

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).

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).

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).

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).

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

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).

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).

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).

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.

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.

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).

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).

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).

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).

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).

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, to appear, , (CSSCI, CSCD).

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.

2021

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).

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).

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).

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).

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).

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).

Bai, Y. X. and Tian, M. Z. (2021). Variable Selection for Sparse Nonlinear Functional Model.Statistical Research, 38 (5):109 – 120. (CSSCI).

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).

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)

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).

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).

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).

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).

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).

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).

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).

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).

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).

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).

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 and Mathematical Sciences, 41(5):1381–1399., (CSSCI).

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 Panel Quantile Regression Model. Journal of Shanxi Normal University (Natural Science Edition), 35 (1):22–28., (CSCD).

Liu, Y. X., Wang, Z. H., Rui, R. X. and Tian, M. Z. (2021). Estimation for Generalized Functional Partially Varying CoefficientHybrid Models. Journal of Systems Science and Mathematical Sciences, 41 (6), 1742-1760, (CSCD).

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).

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).

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).

Tian, Y. Z. and Tian, M. Z. (2021). Bayesian LASSO-Regularized Weighted Composite Quantile Regression with Its Application. Chinese Journal of Applied Probability and Statistics. Vol. 37(4):390–404.

2020

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).

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).

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).

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)

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).

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).

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).

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).

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).

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).

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).

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).

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).

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).

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).

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).

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).

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).

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).

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).

Zhang, C. L. and Tian, M. Z. (2020). Construction of Bootstrap Confidence Intervals Based on Bayes. Statistics and Decision, 1, 32-35, (CSSCI).

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).

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).

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).

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)

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).

2019

Tian, M. Z. and Mei, B. (2019). Tilting Quantile Regression Modeling of Functional Data and Its Applications. Statistical Research, 36 (8), 114 –128, (CSSCI).

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).

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).

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).

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).

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).

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).

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).

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).

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).

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).

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).

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).

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).

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).

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).

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).

Xiong, W., and Tian, M. Z. (2019).Weighted Quantile Regression Theory and Its Application. Journal of Data Science,17(1). P. 145 - 160, (EI).

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).

2018

Tian, M. Z. (2018).Exact Exponential Risk Bounds for Conditional Quantile Regression.

China Sciencepaper, 13(5), 598–610. (CSCD, CA, AJ, CSA, etc.).

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.

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).

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).

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.

Bai, Y. X. and Tian, M. Z. (2018). Functional Analysis of Variance Based on Multiple

Comparison Test, Statistics & Decision, 10, 62–56, (CSSCI).

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).

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).

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).

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).

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).

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).

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).

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).

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).

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

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).

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).

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).

Ma, C. X. and Tian, M. Z.(2017). Financial Impact Analysis for Urban-rural Income Gap in

China based on panel quantileRegression.Journal of Applied Statistics and Management. 36(2), 341–350, (CSSCI, CSCD).

Zhang, T. T., Hu, Y. N., Li, Y. and Tian, M. Z. (2017). Feature Selection Based on Sparse

Clustering with Application ofChina’s Environmental Problems. Statistics & Decision, 4, 18 – 24, (CSSCI).

Li, Z. Y. and Tian, M. Z. (2017). Detecting Change-point via Saddlepoint Approximations,

JournalofSystemsScienceandInformation, 5 (1), 48–73, (CSCD).

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).

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).

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).

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).

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).

Ma, C. X., Tian, M. Z. and Pan, J. X. (2017).Semiparametric Hierarchical Model with

Heteroscedasticity.Statistics and Its Interface, 10, 413–424, (SCI)

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)

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).

Bai, Y. and Tian, M. Z.(2018). Comparison and Application of Several High Dimensional

Variable Selection Methods, Statistics & Decision, 22, 11–16, (CSSCI).

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).

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).

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).

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).

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).

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).

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).

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).

Liang, X. L., Li, E. Q. and Tian, M. Z. (2017). The Parametric Estimation andDiagnostics of

the Multivariate Generalized Poisson Distribution, Journal of Systems Science and Mathematical Sciences, 37(5), 1319–1334, (CSCD).

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).

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).

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).

Rong, Y. H., Tang, M. L. and Tian, M. Z. (2017). Longitudinal Data AnalysisBasedon

Generalized Linear Partially Varying-Coefficient Models . Communicationsin

Statistics – Theory and Methods, 46 (4), 1983 –2001, (SCI, EI).

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).

Tao, L., Zhang, Y. J. and Tian, M. Z. (2017). Adaptive Penalty Quantile Regression for DynamicPanel Data. Journal of Systems Science and Mathematical Sciences, 37 (11), 2245–2259, (CSCD).

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).

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

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).

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).

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.

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).

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).

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).

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).

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).

Xia, W. T., Xiong, W. and Tian, M. Z. (2016). Heteroscedasticity detection and estimation

withquantile difference method. Journal of Systems Science and Complexity,29: 511–530, (SCI, EI, CSCD).

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)

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).

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).

Yan, Z., Dai, X. W. and Tian, M. Z.(2016). Outliers Diagnosis inBig Data Levaraging

Sampling. Journal of Applied Statistics and Management. 35, No.5, 794 – 802, (CSSCI, CSCD).

Huang, Y. L., Zhu, Q. Q. and Tian, M. Z.(2016).Nonparametric Quantile Regression

with Censored Data.Journal of Biomathematics, 3, 387– 407, (CSCD).

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).

Wang, J., Xiong, W. and Tian, M. Z. (2016). A Study on Allocation ofRegional Education

Resources of Beijing. Journal of Mathematics in Practice and Theory, 46(22), 65 – 72, (CSSCI).

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).

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).

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).

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)

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).

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）.

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).

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).

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

Tian, M. Z. (2015). Several Hot Topics in Current Research of Statistical Theory of Big Data.

Statistical Research, vol. 32 (5): 3–12, (CSSCI).

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).

Xiong, W. and Tian, M. Z. (2015). Simultaneous Variable Selection And Parametric

Estimation forQuantile Regression. Journalofthe Korean Statistical Society, 44, 134 –

149, (SCI).

Cao, S. R., Su, Y. N. and Tian, M. Z.(2015). Bayesian Inferenceand Applications in

Hierarchical Models. Statistics & Decision, 423(3), 4–8, (CSSCI).

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).

Wang, Z. and Tian, M. Z.(2015).Semiparametric Mode Regression Based on Locally

Linear Additive Models.Statistical Review, Vol. 9, 124 –142.

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).

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).

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).

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).

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).

Meng, L. B. and Tian, M. Z. (2015).Saddlepoint Approximation to An Important Statistic

Advances in Mathematics. 44 (5): 789–799 . (CSCD, CBST).

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).

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).

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).

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).

Yan, Z. and Tian, M. Z.(2015).An Analysis of Effects of Automobile Exhaust on PM2.5 in

BeijingBased on QuantileRegression. Statistics & Decision. 17, 103–105, (CSSCI).

Zhang, Y. J. and Tian, M. Z. (2015). A QunatileRegession Approach for Estimating Panel

Data Based on K-step Inferences, Journal of Systems Science and Mathematical Sciences 35(9), 1037– 1048, (CSCD)

2014

Xiong, W.andTian,M. Z. (2014). Application of Quantile Regression Techniques in

Linear Heteroscedastic Model. Statistics Review，8, 115–128, (CSSCI).

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).

Xiong, W. and Tian, M. Z. (2014).A Novel Robust and Efficient Tool for Detecting

Heteroscedasticity.Journal of Mathematics and Statistics, 10: 169–185.

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).

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)

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).

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.

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.

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).

Xiong, W. and Tian, M. Z. (2014).Robust Estimators of Scale Function. Journal of

Systems Science and Mathematical Sciences. 34, 703–717， (CSCD).

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).

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).

Tian, Y. Z., Tian, M. Z. and Zhu, Q. Q. (2014).Inference for Mixed Generalized

ExponentialDistribution under Progressively Type-II Censored Samples.Journal of Applied Statistics. 41(3), 660–676 (SCI, SSCI).

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.

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).

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).

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).

Hu, Y. N., Zhu, Q. Q. and Tian, M. Z. (2-13). An Effective Technique of Multiple

Imputationin Nonparametric Quantile Regression. Journal of Mathematics and Statistics. 10 (1): 30–44, 2014.

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

Chen, Y. L. and Tian, M. Z. (2013). Comparative Study of Methods on Longitudinal Data

Analysis. Statistics & Decision, 10， 23–26, (CSSCI).

Tian, Y. Z.,Su, Y. N. and Tian, M. Z.(2013). Optimal Estimation of EXPAR model.

Statistics Review.7，148–156. (CSSCI).

Li, H. F. and Luo, Y. X., Tian, M. Z. (2013).Bayesian Lasso Quantile Regression for

PanelData Models.The Journal of Quantitative & Technical Economics, 30 (2),

138-149.(CSSCI).

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).

Su, Y. N. and Tian, M. Z. (2013).Rolling Quantile Regression Model and Applications.

Statistics Review. 7，124–135.

2012

Tian, M. Z.(2012). Robust Estimation in Inverse Problems via Quantile Coupling. Science

in ChinaSeries A: Mathematics, 55 , 1029–1041.(SCI, EI, CCS, INSPEC,MR, Aerospace Database, MathSciNet, CA， etc.).

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).

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).

Tian, Y. Z. , Tian, M. Z. and Ran, Y. P.(2012). Parameters Estimation of Mixed Inverse

Weibull DistributionsBased on Grouped And Right-Censored Data.Statistics Review. 6, 82–90. (CSSCI).

Tian, Y. Z., Tian, M. Z. and Chen, P. (2012). Parameter Estimation of Mixed Exponential

DistributionwithGrouped and Right-Censored Data. Journal of Applied Statistics and Management, 31 (6), 981-989. (CSCD, CAJCED, CEPS, CJFD, CSSCI).

Tian, Y. Z.,Tian, M. Z. and Chen, P. (2012).Parameters Estimation and Application of

Generalized ExponentialDistributionunderGrouped and Right-Censored Data. Advances in Mathematics, 41(6), 755-762. (CSSCI).

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).

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).

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).

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)

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).

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)

Tian, M. Z., (2012) . The Sentiment of Teaching Methodology in One's Lecturing Life .

University Teaching Quality Quarterly, 3: 44–46.

2011

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).

Tian, M. Z. et al. (2011) Abstract of the International Statistics Forum of 2010. Statistics &

Information Forum. 26, 60–111.

Su, Y. N. and Tian, M. Z. (2011). Adaptive Local Linear Quantile Regression, Acta

Mathematicae Applicatae Sinica (English Series). 27, 509–516, (SCI) .

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).

Li, Z. Y., Liu, S. Band 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

Tian, M. Z., Chan, N. H. (2010). Saddle Point Approximation and Volatility Estimation of

Value-at-Risk, Statistica Sinica, 20, 1239—1256, (SCI, SSCI)

Luo, Y. X. and Tian, M. Z. (2010). Quantile regression for panel data and its simulation

study. Statistical Research. 27, (10): 81–87, (CSSCI).

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)

Zhao, Y. Y., Li, J. P.and Tian, M. Z. (2010). Stride towardthe frontiers of the

international statistical research, promote the reform and development of statistics–4th International Forum onStatistics, Renmin University of China and 5th International Symposium on Frontier of Statistical Science, Statistical Research. 27, (10): 88–112, (CSSCI).

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).

Chen, D. Q. and Tian, M. Z. (2010). A Comparison of Several Different Approaches in

Sliced Inverse Regression. 4, 8–10, Statistics & Decision, (CSSCI).

Tang, M. L. and Tian, M. Z. (2010), Approximate confidence interval construction for risk

differenceunderinversesampling.Statistics and Computing.20，87–98 (SCI, EI).

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

Tian, M. Z., Tang, M. L., Ng, H. K. T.and Chan, P. S. (2009),A comparative study of

confidence intervalsfor negative binomial proportion. Journal of Statistical Computation and Simulation. 79, 241–249 (SCI, SSCI)

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)

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).

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

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).

Tian, M. Z., Tang, M. L., Ng, H. K. T.and Chan, P. S. (2008), Confidence interval

estimators forrisk ratio under inverse sampling.Statistics in Medicine. 27: 3301–3324, (SCI).

Wu. X.and Tian, M. Z., (2008),A longitudinal study of the effects of family background

factors onmathematics achievements using quantile regression. Acta Mathematicae Applicatae Sinica (English Series). 24(1), 85–98. (SCI)

Zhong, Y. and Tian, M. Z. (2008) Bayesian analysis of change-point problems inrare

events. Statistics & Decision. Vol. 3, 38–43. (In Chinese), (CSSCI).

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).

Tian, M. Z., Wu, X., Li, Y. and Zhou, P. (2008), Longitudinalstudy ofthe 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).

Tian, M. Z., Wu, X., Li, Y., and Zhou, P. (2008), Approximate and asymptotic confidence

intervals for epidemiologic rate under inverse sampling. Journal ofSystem Science and Mathematical Science. 28, 513–523, (CSSCI).

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

Tian, M. Z. and Chen, G. M. (2006), Quantile-hierarchical models. Science in China Series

A: Mathematics, 36(10), 1103–1118. (In Chinese), (CSSCI).

Tian, M. Z. (2006), A quantile regression analysis of family background factor effects on

mathematical achievements, Journal of Data Science, 4, 461–478, (EI).

Tian, M. Z. and Chen, G. M. (2006), Hierarchical linear regression models forconditional

quantiles.Science in China Series A: Mathematics, 49, 1800–1815.(SCI, EI)

Tian, M. Z. (2006), Two stages inferences for a semi-parametric regression model. Acta

Mathematicate Applicate Sinica, 29， 601–608, (CSSCI).

2005

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).

Tian, M. Z.(2005), Estimation theory based on quasi-residuals insliced inverse regression,

Journal of Systems Science and Mathematical Sciences, 25, 348–355, (CSSCI).

2004

Tian, M. Z. and Li, G. Y. (2004), Quasi-residuals method in sliced inverse regression,

Statistics and Probability Letters, 66, 205–211. (SCI)

2003

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

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

Tian, M. Z. and Wu, X. Z. (2001), A quasi-residuals method, Advances in mathematics, 30,

182–184, (CSSCI, SCI).

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

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

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).

Si, S. J., Pan, J. X.and Tian, M. Z. (2012). Robust Estimation for Joint Mean-Variance

Models. (underreview)

Tian, M. Z., Zhang, H. P.(2012). Parametric Modeling for Complex Large-scale Genetic

Data Sets with Multiple Ordinal Traits, (Submitted), (SCI).

Tian, M. Z.(2012). Locally Adaptive Quantile Regression And Its Applications, Journal of

the American Statistical Association. (No. JASA-T10-045 ), Under revision.(SCI)

Han, J. L., Pan, J. X. and Tian,M.Z. (2012).Parameters estimation in nonlinear

reproductive dispersion mixed models. (Under revision：No. 10109).

Tian, M. and Härdle, W. (2012).Locally varying bandwidth selection for conditional

quantile regression.(Under review).

Tian, M. Z. andChen, G. (2010). A limit distribution for the maximum of weighted sums

of m-dependent random variables. (Under review).

Feng, D. D. and Tian, M. Z. (2013).Nonparametric quantile regression with censored

data. (Under review)

Li, Q. andTian, M. Z. (2013). Locally smoothing composite quantile regression based on

semiparametric models. (Under review)

Lv, S and Tian, M. Z. (2013). Generalized varying coefficient mean covariance regression

methods for longitudinal data. (Under review)

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)

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)

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)

Xiong, W. and Tian, M.Z.(2014). Reweighted efficient estimation in varying coefficient

models (SCI)

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)

Tian, Y. Z. and Tian, M. Z.(2014).Estimating Mixed Exponential Distributions under

Hybrid Censoring , Scandinavian Journal of Statistics.(SCI)

Li, E. Q. and Tian, M. Z.(2014). Hierarchical Spline Models for Conditional Quantiles and

the Air Quality Index of Beijing. (CSSCI).

Liang, X. L. and Tian, M. Z.(2014). The Estimation of Epidemiological Rate under Inverse

Sampling Estimation Based on Hierarchical Models, under review, (CSSCI).

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).

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).

Xiong, W. and Tian, M. Z.(2014). A New Robust Regression Method Based on Sparsity

Function, under review, (SCI).

Li, E.Q. and Tian, M. Z. (2014), Hierarchical Spline Models for Conditional Quantiles and

The Air Quality Index of Beijing, under review, (SCI).

Yang, Y. Q. and Tian, M. Z. (2014), Quantile Regression Based on Single Index

Models for Longitudinal Data, under review, (CSSCI).

Ma, C. T and Tian, M. Z. (2014), Nonlinear Mixed Effects Model of ROC and Its

Medical Applications, under Review, (CSSCI).

Tian, M. Z., Tang, M. L., and Chan, P. S. (2010).Saddlepoint approximations to

conditional probability integral in metal analysis. (Under review).

Tian, M. Z. (2010).A limit distribution for the generalized Erdös-Kac Statistic. (Under

review)

Meng, L. B. and Tian, M. Z. (2015). Semi-parametric Nonlinear Mixed Effects Models

Based on Saddlepoint Approximation, (SCI).

Tian, M. Z. (2015).Several Hot Topics In Current Research of Statstical Theory of Big

Data Statistical Research, 2014–1617 , (CSSCI).

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)

Tian, Y. Z., Han, X. F. and Tian, M. Z.(2015). Estimating Mixed Exponential

Distributions under Hybrid Censoring , Statistical Methodology .(SCI)

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).

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).

Yuan, M. and Tian, M. Z. (2015). State Space Mixed Model for Negative Binomial Responses.

Under review, (CSSCI).

Shi, P. X. and Tian, M. Z. (2015). Bayesian Inference for Dynamic Zero-inflated Poisson

Model. Under review, (CSSCI).

Meng, L. B. and Tian, M. Z. (2015). Confidence Intervals Construction for Odds Ratio under

Binomial Sampling Based on Saddlepoint Approximation. Under review, (CSSCI).

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).

Zhang, Y. L. and Tian, M. Z. (2016). Parameter Estimation of Zero-Inflated Poisson Model

Based on Probit Regression. Statistical Review.

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).

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)

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).

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.

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).

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).

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).

Gu, M. C. and Tian, M. Z.(2016). Periodic Spatial-Temporal Quantile Model with Varying

Coefficients, Computational Statistics, No. COST-D-17-00325, (SCI).

Yuan, B. and Tian, M. Z. (2016).Mixed Copula Based on Empirical Distribution and

Its Applications to Financial Risk Management , Statistical Research, (CSSCI).

Qian, M. L. and Tian, M. Z. (2016).Analysis on Influencing Factors of PM2.5 in

Beijing BasedonQuantile Regression, Forcasting, (CSSCI).

Wang, S. and Tian, M. Z. (2016).A Non-linear Hierarchical Growth Curve Model for

Forecasting the Outstanding Claims Reserves, Economic Management Journal，(CSSCI).

Zhang, W. S. and Tian, M. Z.(2016). Statistical Analysis of the Survival Rule of Electrical

Vehicles, Statistics & Information Forum, , (CSSCI, RCCSE).

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.

Yan, Z. and Tian, M. Z.(2016). A Novel Testing Tool for Heteroscedasticity Using

Double Kernel Approach. Test, SEIO-D-16-00138, (SCI).

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)

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).

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)

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)

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).

Sun, W. B., Wang, L. and Tian, M. Z.(2016). The Determinants of Resident Income

Based on Classification Trees. Economic Review, (CSSCI).

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).

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).

Mei, B. and Tian, M. Z.(2016). Tilting Quantiles for Functional Data Based on Sparse

Smoothing, Biometrika, No. BIOMTRKA-16-478, (SCI).

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).

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).

Tian, Y. Z., Wu, X. Q., and Tian, M. Z.(2016). A Gibbs Sampling Algorithm For Bayesian

Weighted Composite Quantile Regression. Journalofthe Korean Statistical Society, under review, (SCI).

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).

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).

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).

Xiong, W. and Tian, M. Z.(2014). Hybrid Weighted Quantile Regression, Journal of Applied

Statistics , No. CJAS-2017-0918, under review, (SCI).

Li, E. Q., Dai, X. W. and Tian, M. Z. (2016). Variable Selection Based on Ultrahigh

Dimensional Competing Risks Models., (No.) , ( ).

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).

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) .

Xia, L. L. and Tian, M. Z. (2018). Employee Turnover Forecast Based on Lasso-Logistic

Regression Model. Statistics & Information Forum, No., -.under review, (CSSCI).

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).

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).

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).

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).

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).

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).

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).

Rui, R. X. and Tian, M. Z. (2019). A Novel Quantile Test Based on Percentile Deviation. Chinese Annals of Mathematics, _A(2): – ，(CSCD, CSCI).

Tai, L. N., Tao, L. and Tian, M. Z. (2020). Bayesian Semiparametirc Quantile Sample

Selection Model with Heterogeneity, ActaMathematicaSinica , (.),–, , (SCI).

Zhang, R. X. and Tian, M. Z.(2019). Sliced Inverse Quantile-based Regression for

Dimension Reduction, Journal of…,, under review, (SCI).

Su, P. and Tian, M. Z.(2019). Censored Quantile Correlation Screening, Biometrics , No.

BIOM2019679M , under review, (SCI).

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).

Han, Z. K. and Tian, M. Z.(2019). Research on Fraud Detection Models in Third Party

Payment, Journal of…,, under review, (CSSCI).

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).

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).

Yan, M. B. and Tian, M. Z. (2019). The Oracle Properties of Adaptive Lasso under Selective

Inference Scheme. Journal of…,, under review, (CSCD).

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).

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).

Zhang, C. L. and Tian, M. Z. (2019). Construction of Bootstrap Confidence Intervals Based on Bayes. Statistics and Decision, No. 190715011, to appear, (CSSCI).

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).

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).

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).

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).

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).

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).

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).

Li, C. Y. and Tian, M. Z. (2019). Resampling Algorithm Based on Algorithmic Leveraging in

Big Data Analytics. Statistical Research, under review, (CSSCI).\

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).

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).

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).

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).

Xiong, W. and Tian, M.Z.(2020).An Innovated Attributes-Benefit Latent Space Model for Directed Scale-Free Networks, Social Networks, (1): – , (SCI).

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).

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).

Tian, Y. Z. Tang, M. L. and Tian, M. Z. (2020).Bayesian Joint Regularized Quantile

Regression Inference for Multi-Response Linear Regression Model.

Liang, J. W. and Tian, M. Z. (2020). Imputed Tensor Regression for Spatial-temporal Data. Journal of Multivariate Analysis, JMVA_2021_, under review, (SCI).

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).

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).

Qian, Z., Luo, Y. X., Zhao, X. Y. and Tian, M. Z. (2021). ….. Journal of Applied Statistics and

Management, , –, (CSSCI, CSCD).

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).

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).

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).

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).

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.

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).

Rui, R. X. and Tian, M. Z. (2021). Non-iterative Gaussianization. Journal of Computational and Graphical Studies, No.GCGS-21-188, under review, (SCI).

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).

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).

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).

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).

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).

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).

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).

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).

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).

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).

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).

Kurbanyaz, G, and Tian, M.Z. (2021). Generalized Method of Moments Estimation ofSemi-

parametric Spatially Varying Coefficient Error Autocorrelation Regression Model. SCIENCE CHINA Mathematics, No. SSM-2022-0004, under review, (SCI).

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).

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).

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).

Tai, L. N., Tao, L., Pan, J. X., Tang, M. L., Yu, K. M., Härdle, W. K andTian, 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).

Bai, Y. X. and Tian, M. Z. (2022). Variable selection for censored grouped heterogeneous mixture Model. Working paper,–, (SCI).

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).

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).

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).

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).

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).

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).

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).

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:)

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).

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).

Guo, J. X. and Tian, M. Z.(2022). Smoothed Quantile Regression and SIR Algorithm with

Nonignorable Nonresponse. Acta Mathematicae Applicatae Sinica, … (02):14-?, (CSCD).

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.

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).

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).

Liang, J. W. and Tian, M. Z. (2023). Sequential Thresholded Quantile Estimator for Sparse Regression. Journal of the Korean Statistical Society, under review, (SCI).

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).

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).

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).

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.

Wang, W. X., Zhang, J. J. and Tian, M. Z. (2023). Variational Bayesian Regularization Quantile Regression. Applied Mathematics-A Journal of Chinese Universities, , –, (CSCD).

Guo, J. X. and Tian, M. Z.(2023).Semiparametric Bayesian quantile regression for non random missing data. Statistical Research, ? (5):?– ?. (CSSCI).

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).

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).

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).

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.

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.

Kong, F. S., Wang, Z. H. and Tian, M. Z. (2023). Functional time-varying coefficient Cox

model and its application. Statistical Research, 38 (?): ?-?, (CSSCI).

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).

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, Q1)

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)

Hou, J., Liu, S. and Tian, M. Z. (2023). Research on Partial Linear Geographically Weighted

Quantile Regression Model, Statistical Research, 3 (?): ?-?, under review, (CSSCI).

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).

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).

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).

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).

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).

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).

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).

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).

Zhao, X. Y., Rong, Y. H. and Tian, M. Z. (2024). Garrotized kernel machine in semiparametric quantile regression, under review, (SCI).

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).

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).

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).

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).

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).

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.

Sun, P. F., Zhang, Z. and Tian, M. Z. (2024). Causal Effect Analysis of Advanced Manufacturing Clusters on New Quality Productivity: An Examination Based on Double Machine Learning, No. J24102913, Journal of Technology Economics.

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).

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).

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).

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).

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).

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).

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).

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).

Zhang, L. P. and Tian, M. Z. (2024). Zero-inflated Tests and Applications in Geometric Regression Modeling. No. 20240614001,Under review, (CSSCI).

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).

Tang, X. P., Tian, Y. Z., Wang, Y. and Tian, M. Z. (2024). Zero -Truncated Bell Regression Modeling and Its Application to Analyze Adolescent Generalized Anxiety Disorder Data. Transactions on Modeling and Computer Simulation, ID:TOMACS-2024-0059, under review, (SCI).

Tian, Y. Z. and Tian, M. Z. (2024). A Class of Zero-Truncated Bell-Touchard Count Distributions and Its Applications to An Adolescent Generalized Anxiety Disorder Data. ESAIM: Probability and Statistics, under review, (SCI).

Li, J. Y. and Tian, M. Z. (2024). Research on the Influence of the Digital Economy on the Consumption of Rural Residents—Empirical Analysis Based on Panel Quantile Regression. Statistical Research, No. 20240626009. (CSSCI).

Jiang, K. and Tian, M. Z. (2024). Impact of Non-agriculturalization on Carbon Emission of Chinese Counties, Journal of Applied Statistics and Management, No.24-?, (CSSCI, CSCD).

Lin, Q. J. and Tian, M. Z. (2024). Research on the Impact of Industrial Structure Transformation and Upgrading on High Quality Economic Development. Journal of Finance and Economics. No. 2024-01757, (RCCSE).

Zhang, H. X., Tian, Y. Z., Wang, Y. and Tian, M. Z. (2024). The Joint Quantile Regression Modeling of Mixed Ordinal and Continuous Responses with Its Application to An Obesity Risk Data, Statistical Methods in Medical Research. No. SMM-24-0281.R1. (SCI).

Liu, S., Hou, J., Meng, T. and Tian, M. Z. (2024). Quantile Tensor Regression with Region Selection, Statistics and Computing. No. (SCI).

Zhang, L. P., Kurbanyaz, G. and Tian, M. Z. (2024). A new statistical test based on inflated zeros in right-censored geometric regression models. Biometrical Journal, No. bimj.202400233, (SCI).

Rui, R. X., Yu, K. M., Pan, J. X., Li, Q. L. and Tian, M. Z. (2024).ON Functional Partial Least Squares for Scalar-on-multiple-function Regression. Statistical Sinica. No. SS-2024-0302, (SCI)

Zhang, J. J., Wang, W. X. and Tian, M. Z. (2024). Variational Bayesian Variable Selection in

Logistic Regression Based on Spik-and-slab Lasso. Journal of Systems Science and

Mathematical Sciences, No. 240719, (CSCD)

Wang, W. X. and Tian, M. Z. (2024).Variational EM Algorithm for Quantile Regression in

Mixed Effects Models. Mathematics, No. mathematics-3229156, (SCI, Q1).

Tian, Y. Z., Wang, Y. and Tian, M. Z. (2024). The Classification Algorithm Based on

Functional Logistic Regression Model with Spatial Effects and Its Application in Air Quality

Analysis, Statistical Analysis and Data Mining, No. SAM-24-389, (SCI).

Cai, X. R., Tian, Y. Z., Wang, Y. and Tian, M. Z. (2024). The Classification Algorithm of Spatial Functional Probit Model and Its Application to Air Quality Analysis in the Beijing-Tianjin-Hebei Region, Computational Statistics, No. COST-D-24-00547, (SCI).

Yu, Z., Yu, K. M. and Tian, M. Z. (2024). Penalized Longitudinal Parametric Quantile

Regression for Analyzing the Determinants of Life Expectancy, Journal of the Royal Statistical Society, Series B: Statistical Methodology, Manuscript ID JRSSB-Feb-2024-???, (IF, 5.9, SCI, Q1).

Hu, Y. N., Qu, X. H., Guo, S. H. and TIian, M. Z. (2024), Double Machine Learning

Estimation and Variable Selection for The Spatial Quantile Regressive Model, Journal of

Systems Science and Mathematical Sciences, (No. ), under review, (CSCD).

Meng, T., Liu, S. and Tian, M. Z. (2024). Tensor Quantile Regression with Exponential-type Penalty. Statistical Research, No. 20240…., under review, (CSSCI).

Liu, M. R., Yu, Z., Kong, F. S. and Tian, M. Z. (2024) Spatiotemporal Dynamic Quantile Regression Model with a Latent Gaussian Process, under review, (SCI).

Tian, Y. Z., Niu, X. Y., Wang, Y. Tian, M. Z. and Wu, C. H. (2024). Joint Conditional Quantiles Inference of Multivariate Response Regression Model with VAR(q) Error and Its Application in Evaluating Energy Efficiency,Econometrics and Statistics, No. ECOSTA-D-24-00181, under review, (SCI).

Hu, Y. N., Xu, G. F. and TIian, M. Z. (2024), Research on the Model of Quantile Treatment Effects for Multiple Policies Based on Covariate-Adaptive Randomization and Its Application, Statistical Research, (No. ), under review, (CSSCI).

Teaching

Postgraduate courses (Renmin University of China)

Statistical Models (3 hours)

Quantile Regression (2 hours)

Hierarchical Models (3 hours)

Modern Statistical Theory and Methods (2 hours)

Saddlepoint Approximations (2 hours)

Statistical Estimation of Epidemiological Risk (2 hours)

Statistical Analysis with Complex Data (2 hours)

Frontiers in Statistics (2 hours)

Computer Intensive Methods (2 hours)

Quantitative Risk Management (3 hours)

Advanced Statistics (3 hours)

The Fundamental Advanced Statistics for Phd Students (3 hours)

High Dimensional Data Analysis (2 hours)

Statistical Modeling (2 hours)

Statistical Diagnostics (3 hours)

Undergraduate course (The Renmin University of China)

Statistical Computation (2 hours)

Regression Analysis (3 hours)

Statistical Diagnostics (3 hours)

Mathematical Statistics (3 hours)

Multivariate Statistical Analysis (3 hours)

Faculty Positions

Assistant, China Insurance University (1994)

Associate professor, Renmin University of China (2004)

Full professor, Renmin University of China (2008-present)

Distinguished Professor of Lanzhou University of Finance & Economics, The Project of Flying Apsaras Scholar of Gansu Province (2013-present)

Students Supervised (selected)

PH.D STUDENTS SUPERVISED

2017

Yongxin Bai (白永昕)：978981639@qq.com

Li Tao (陶丽)：18810684228@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

2015

Liwen Xu (徐礼文)：xulw163@163.com

2014

Zonghu Wang (王纵虎)：zonghuwang@petrochina.com.cn

MASTER STUDENTS SUPERVISED

2016

LingxinDang (党领欣): danglingxin@163.com

Tingting Li (李婷婷): 18037217803@qq.com

Yijian Liu (刘一鉴): muse726@163.com

Peng Su (苏鹏):503545157@qq.com

Lan Yang (杨澜): yanglan14991@163.com

Ying Yu (余颖):1764785945@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)： 512620510@qq.com

2015

Xiaoshen He (何晓申)：skss309@163.com

Yarong Wang (王亚荣)：963492308@qq.com

Yanfei Jia (贾燕飞)：973976831@qq.com

Ye Liu (刘烨)：465499119@qq.com

Manling Qian (钱曼玲):894154717@qq.com

Li Tao (陶丽)：18810684228@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):331433671@qq.com

Shaoyang Li (李少洋): li.shaoyang.lsy@gmail.comli.shaoyang@yahoo.com

Xintao Tian (田鑫涛): xttian90@126.com

Shan Wang（王珊）： 476975074@qq.com

Bo Yuan (袁博)：yb1992yuanbo@163.com

Yuanjie Zhang (张元杰)：jianyouyan@163.com

Yongxin Bai (白永昕)：978981639@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): luojing839036277@qq.com

Puxin Shi (史普欣)：gonewday@163.com

Xiaohe Wang (王晓荷) wxh1234____@hotmail.com

Meng Yuan (袁梦)：2013102866@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)：tongji20072011@163.com

Yanan Hu (胡亚南)：yananhu@139.com

Yali Huag (黄雅丽)：642472396@qq.com

Qian Li (李茜)：lily29.lee@gmail.com , sukikazuya@126.com

SuqianLiu (刘甦倩): vivian890721@sina.com

ShuangLv (吕爽)：15830698739@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)：05271064@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)：apple04072430@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

2004

ChuannengHuan (黄传能)：cnhuang_2008@163.com

Tian Chen (陈甜)：trollycn@gmail.com, chenvanessa999@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)han198706291aa@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

larry于 2013年11月16日 10:30:09发送给 mztian@ruc.edu.cn完整信息 2011

Zhangzhi Cao (曹彰之):caozhangzhi@ruc.edu.cn

Jie Song (宋洁): jone_song@163.com; 499170335@qq.com

Jia Wang (王佳): wangjia_1993@163.com

Shuang Wang (王爽): 18810310869@163.com

Taotao Zhang (张陶陶): zhangtaotao604@163.com

2012

Yue Bai (白玥): baiyue@ruc.edu.cn

Yuan Mei (梅园): 1064389901@qq.com

Wensha Zhang (张文莎): 641761367@qq.com

2013

Yuanfang Qiao(乔媛芳): 597979303@qq.com

Yongxin Shuai (帅咏昕):shuai.yongxin@163.com

Ke Wang (王可):853885892@qq.com

Lan Wang (王岚):2996306800@ruc.edu.cn

Chenling Yang (杨晨泠): annabelyang@qq.com

Qi Zheng (郑琪): preciousnereus@163.com

2014

Yuqing Lu (芦雨晴): 15010788672@163.com

Yurong Wang (王宇榕): muliwyr@163.com

VISITING SCHOLARS SUPERVISED

2016

Jing Guo (郭晶)：497941022@qq.com

2014

Chahua Ye (叶茶花)：893954843@qq.com

2011

Yanping Ran (冉延平)：yanpingran@sina.com

2009

Junlin Han (韩俊林)：hanjunlin001@vip.163.com

Honors and Awards

2010Recipient of the first prize for excellent scientific research fruitsof the National Chinese Statistical Bureau.

2010Recipient of the third prize for excellent courseware fruitsof the National Chinese Statistical Bureau.

2010Recipient of the prize for excellent scientific research fruitsof the Beijing Municipal Statistical Bureau.

2008Recipient of the second prize for excellent scientific research fruitsof the National Chinese Statistical Association.

2006Excellent person of the Ministry of Education of the People’s Republic of China in the new century.

2006Recipient of the second prize for excellent scientific research fruitsof the National Chinese Statistical Association.

1991-1992 Outstanding Teacher.

Professional Activity (selected)

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）andThe 1st Symposium, Invited speaker,Anhui NormalUniversity, 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 TheChinese Association for Applied Statistics （CAAS）andSymposium 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 onData Mining & Business Intelligence and TheSymposium 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 ofAcademic report， Invited speaker,Lanzhou University, Lanzhou, Gansu, China, September 16, 2014.

15)“Statistical Analysis of High Dimensional Data with Hierarchical Strucutre”. A Series ofAcademic 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”. TheNational Statistical Symposiumof 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 InternationalConference 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.

Professional membership

Associate Editor of Statistical Review

Secretary General ofChinese Survival Analysis Association

Vice Director of Centered Applied Statistics, Renmin University of China,Key Research Institute of Humanities and Social Sciences at Universities

The Membership of Chinese Society of Probability and Statistics

The Membership of Econometric Society (ID. 1734779 )

The Membership of the American StatisticalAssociation (ID. 165873)

The American Educational Research Association

Referee for more than 50 International Journals

Computer skills

S-PLUS,MATLAB, MLwiN, HLM, SPSS, R, MATHEMATICA.

Microsoft Office, Latex.

Current cooperative projects abroad

The Project 1 (with Prof. Dr. Wolfgang Karl Härdle, Humboldt university ): Locally adaptive methods for the modern quantile regression.

The Project 2 (with Prof. Dr. Peter Hall, University of Melbourne): Background:The projects are all in nonparametric statistics, and include topics in functional data analysis, inverse problems and classification, variable selection and hypothesis testing for very high dimensional data. Combinations of these areas, for example classification methods for functional data, or variable selection in the presence of errors in variables, are also included. Objectives:(a) Development of new statistical methodology in the fields described above; (b) Application of the methodology to real data; (c) Development of theoretical tools appropriate to describing the performance of the methodology in (a), and development of appropriate optimality theory; and (d) Exploration of numerical performance of the methodology, through simulation studies.

Current grants

The National Natural Science Foundation of China (No.11271368)

Project supported by the Major Program ofBeijing Philosophy and Social Science Foundation of China (No. 15ZDA17)

Project of Ministry of Education supported by the Specialized Research Fund for the Doctoral Program of Higher Education of China (Grant No. 20130004110007)

The Key Program of National Philosophy and Social Science Foundation Grant (No. 13AZD064)

The Fundamental Research Funds for the Central Universities, and the Research Funds of Renmin University of China (No. 15XNL008)

The Project of Flying Apsaras Scholar of Lanzhou University of Finance & Economics

Dr. Tian is particularly interested in developing appealing statistical approaches and their applications. He also takes delight in sophisticated statistical models. In addition, he has been made interdisciplinary collaborations with others abroad for several years.