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2023年研究成果

  1. Liu Wei, Huazhen Lin*, Shurong Zheng* and Jin Liu. (2023), Generalized factor model for ultra-high dimensional correlated variables with mixed types. Journal of the American Statistical Association. 118, 1385-1401.

  2. Luo, L., Zhou, L. and Song, P.X.K. (2023). Real-time regression analysis for streaming clustered data with possible abnormal data batches. Journal of the American Statistical Association , 118, NO. 543, 2029–2044

  3. PETER X.-K. SONG,AND LING ZHOU,2023,Discussion of(Statistical inference for streamedlongitudinal data',Biometrika,110, 4, pp. 859–862

  4. Ye He#, Ling Zhou#, Yingcun Xia and Huazhen Lin*.2023,Centre-augmented L2-type regularization for subgroup learning. Biometrics. 79, 2157-2170.

  5. Chenlin Zhang, Huazhen Lin*,Li Liu, Jin Liu and Yi Li (2023). Functional data analysis with covariate-dependent mean and covariance structures. Biometrics. 79, 2232-2245.

  6. Song Xi Chen, Bin Guo, Yumou Qiu*,2023,Testing and signal identification for two-sample high-dimensional covariances via multi-level thresholding, Journal of Econometrics 235,1337–1354

  7. Ling Zhou, Xichen She and Peter X.K Song. (2023), Distributed empirical likelihood approach to integrating unbalanced datasets Statistica Sinica,33,2209-2231

  8. Wei Liu,Huazhen Lin*. Li Liu, Yanyuan Ma, Ying Wei and Yi Li (2023). Supervised structural learning of semiparametric regression on high-dimensional correlated covariates with applications to eQTL studies. Statistics in Medicine. 42,3145-3163.

  9. Huazhen Lin, Shuangxue Zhao, Li Liu*, Wenyang Zhang (2023). Structured Ultrahigh Dimensional Multiple-Index Models with Efficient Estimation in Computation and Theory. Statistica Sinica. 33, 2137-2160.

  10. Lei Bo, Lan Wei, Fang Nengsheng, Zhoujing, Polynomial network autoregressive models with divergent order, Science China Mathematics,66, pages 1073–1086

  11. Rui She. (2023). Tests of Unit Root Hypothesis with Heavy-tailed Heteroscedastic Noises,Statistica Sinica,33, 215-236

  12. Xuetong Li, Feifei Wang, Wei Lan, and Hansheng Wang, 2023, Subnetwork estimation for spatial autoregressive models in large-scale networks,Electronic Journal of Statistics,Vol. 17,1768–1805

  13. Zhuo Tan, Yifan Zhu, Bin Liu,2023, Learning spatial-temporal feature with graph product, Signal Processing 210 (2023) 109062

  14. Liang Wu, Weifang Zhang*, 2023, Co-movement between RMB and Bitcoin with Effects of DCEP Using Wavelet Coherence Analysis, Fluctuation and Noise Letters, Vol. 22, No. 4 (2023) 2340010 (13 pages)

  15. Jiamin Liu, Wangli Xu, Fode Zhang, and Heng Lian,2023, Properties of Standard and Sketched Kernel Fisher Discriminant, IEEE Transactions On Pattern Analysis And Machine Intelligence, VOL. 45, NO. 8, AUGUST 2023

  16. WeiLiu, LanLuo, LingZhou,2023,Online missing value imputation for high-dimensional mixed-type data via generalized factor models, Computational Statisticsand Data Analysis 187,107822

  17. Weijia Zhang, Wanni Lei* & Xiaojun Zhu,2023,A novel model of the continual reassessment method in Phase Itrial, Scientific Reports,13:5047

  18. Zhang Fode , Hon Keung Tony Ng and Lijuan Shen,2023, Robust Estimation and Selection for Degradation Modeling With Inhomogeneous Increments, IEEE TRANSACTIONS ON RELIABILITY,(99):1-16

  19. Bin Liu,Jiujun He,Ziyuan Li,Xiaoyang Huang,Xiang Zhang*,Guosheng Yin∗,2023, Interpret ESG Rating’s Impact on the Industrial Chain Using Graph Neural Networks, Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence (IJCAI-23), 6076- 6084

  20. Lu Wei, Bin Liu, Jiujun He, Manxue Zhang, Yi Huang,2023, Autistic Spectrum Disorders Diagnose with Graph Neural Networks, Proceedings of the 31st ACM International Conference on Multimedia, Pages 8819–8827

  21. Min Zhou, Mingwei Dai*, Yuan Yao, Jin Liu, Can Yang and Heng Peng,2023,BOLT-SSI: A statistical approach to screening interaction effects for ultra-high dimensional data, Statistica Sinica, v. 33, (4), 2327-2358

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