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2015年研究成果

1.Jing Zhou, On KitTam, and Wei Lan (2015),“Are investor protection and ownership concentration substitutes inChinese family firms?”Emerging Markets Finance and Trade, 51,432—443.

2.Wei Lan, RonghuaLuo, Chih-Ling Tsai, Hansheng Wang, and Yunhong Yang (2015),“Testing theDiagonality of a Large Covariance Matrix in a Regression Setting,”Journal ofBusiness & Economic Statistics, 33, 77—86.

3.Yingying Ma, Wei Lan,and Hansheng Wang (2015),“Testing predictor significance with Ultra high dimensionalmultivariate responses,”Computational Statistics & Data Analysis, 83, 275—286.

4.罗荣华,兰伟,杨云红(2015),“基金排名与主动性水平:理论与实证,”中国管理科学,2015年第8期,158—167.

5.Yingying Ma, Wei Lan,and Hansheng Wang (2015),“A High Dimensional Two-Sample Test under a Low Dimensional FactorStructure,”Journal of Multivariate Analysis, 140,162—170.

6.Jinyuan Chang and PETER HALL (2015) Double-bootstrap methods that use a single double-bootstrapsimulation , Biometrika , 102, 1. 203–214

7.Jinyuan Chang, SongXi Chen,∗, Xiaohong Chen(2015)Highdimensional generalized empirical likelihood for moment restrictions withdependent data,Journal of Econometrics,185,283-304

8.Chen, X., Alan Wan,and Zhou, Y.(2015). Efficient quantile regression analysis with missingobservations. Journal of the American statistical Association,110, 723-741.

9.Hu,N., Chen, X.*and Sun, J.(2015) Regression analysis of length-biased and right-censoredfailure time data with missing covariates. Scandinavian Journal of Statistics,42, 438-452.

10.Chen, X.*, Sun, J. and Liu, L.(2015) Semiparametric partial Linear quantile regression of longitudinal data with time varying coefficients and informative observation times. Statistics Sinica,25, 1437-1458.

11. ShaogaoLv*. (2015). Refined generalization bounds of gradient learning overreproducing Kernel Hilbert spaces . Neural Computation, (27), 1294–1320.

12. ShaogaoLv* and Fanyin Zhou. (2015). Optimal learning rates of L^p-type multiple kernellearning under general conditions. Information Science, (10) 255-268.

13. ChaoZhang and Shaogao Lv*. (2015). An efficient kernel learning algorithm for semisupervisedregression problems. Mathematical Problems in Engineering, Volume 2015, ArticleID 451947, 9 pages.

14. 好奇,林华珍*,张兴凤,朱玉峰,张伟(2015).基于混合效应模型的医保费用测算及监控。《数理统计与管理》,34,1040-1047。

15. Jinyuan Chang,Bin Guo, Qiwei Yao*(2015) High dimensional stochastic regression with latentfactors, endogeneity and nonlinearity ,Journal of Econometrics ,189 297–312

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