2014年：
1. Huazhen Lin, Ling Zhou, Chunhong Li, Yi Li,（2014） Semiparametric transformation models for semicompeting survival data. Biometrics. 70（3）599-607.
2. Huazhen Lin, Ling Zhou and Xiao-Hua Zhou. （2014）Semiparametric regression analysis of longitudinal skewed data. Scandinavian Journal of Statistics. 41（4）1031-1050.
3. Ling Zhou, Huazhen Lin, Xin-Yuan Song and Yi Li, （2014）Selection of latent variables for multiple mixed-outcome models. Scandinavian Journal of Statistics. 41（4）1064-1082.
4. Huazhen Lin, Ling Zhou, Robert M. Elashof, Yi Li (2014). Semiparametric latent variable transformation models for multiple mixed outcomes. Statistica Sinica, 24 , 833-854.
5. Huazhen Lin, Yi Li, Liang Jiang and Gang Li(2014). A semiparametric linear transformation model to estimate causal effects for survival data. Canadian Journal of Statistics, 42, 18-35.
6.Yue Liu,Bingjie Wang and Shaogao Lv.(2014) Using multi-class adaboost tree for prediction frequency of auto insurance. Journal of Applied Finance & Banking, (4), 45-53.
7. Liu Shuangzhe, Ma Tiefeng, （2014）Polasek Wolfgang, Spatial system estimators for panel models: A sensitivity and simulation study. Mathematics and Computers in Simulation, 101 78-102.
8. Ma Tiefeng, Liu Shuangzhe, Ahmed, S. Ejaz, （2014）Shrinkage estimation for the mean of the inverse Gaussian population. Metrika, 77(6) 733-752.
9. Ma Tiefeng, Liu Shuangzhe, （2014）Pitman closeness of the class of isotonic estimators for ordered scale parameters of two Gamma distributions. Statistical Papers,55(3) 615-625.
10. Ye Rendao, Ma Tiefeng, Luo Kun，（2014）Inferences on the reliability in balanced and unbalanced one-way random models. Journal of Statistical Computation and Simulation, 84(5) 1136-1153.
11.Si, Y., Liu, P., Li, P., Brutnell, T.P. (2014) Model-Based Clustering for RNA-Seq Data, Bioinformatics, 30(2): 197-205
12. Wei Lan, Hansheng Wang and Chih-Ling Tsai (2014), “Testing Covariates in High Dimensional Regression,” Annals of the Institute of Statistical Mathematics， 66, 279—301.
13. Jianqing Fan, Yunbei Ma* and Wei Dai (2014), Nonparametric Independence Screening in Sparse Ultra- High Dimensional Varying-Coefficient Models, Journal of the American Statistical Association,109（507）1270-1284
14. Yunbei Ma, Alan Wan, Xuerong Chen and Yong Zhou (2014), On estimation and inference in a partially linear hazard model with varying coefficients, Annals of the Institute of Statistical Mathematics, 66: 931-960.
15、Zhang Shulin, Wei Zhenghong, Bi Qiuxiang,(2014),A linear IBD model and its statistical inference, Chinese Quarterly Journal of Mathematics,29(3):356-362.
16、张术林，(2014), 评估Value-at-Risk模型—条件矩检验方法，系统工程理论与实践，34(5):1153-1160.
17.Yunbei Ma and Xuan Luo (2014), New Inference Procedures for Semiparametric Varying-Coefficient Partially Linear Cox Models, Journal of Applied Mathematics. vol. 2014, Article ID 360249, 16 pages.
18. Shaogao Lv and Fanyin Zhou. (2014) Optimal learning rates of L^p-type multiple kernel learning under general conditions. Information Science, 294 (2015) 255–268
19.Jiandong Chen, Yaqing Si, Fengying Li and Aifeng Zhao "An Analysis of Relationship among Income Inequality, Poverty and Income Mobility--Based on Distribution Functions," 2014 Abstract and Applied Analysis. Volume 2014, Article ID 186564, 10 pages
20.Yingying Ma， and Wei Lan (2014), “Testing predictor significance with Ultra high dimensional multivariate responses,” Computational Statistics & Data Analysis, Minor Revision.83（2015）275-286
21.Chen,X.,Wan, A. andZhou, Y.(2014)A quantile varying-coefficient regression approach tolengthbiased data modeling. Electronic Journal of Statistics , 8, 2514-2540.
