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2022年学术成果

  1.  Chang, J., Kolaczyk, E. D., & Yao, Q. (2020). Estimation of subgraph densities in noisy networks. Journal of the American Statistical Association, 117,537.361-374

  2. Huazhen Lin*, Jiaxin Liu, Haoqi Li, Lixian Pan and Yi Li (2022). Efficient Estimation and Computation in Generalized Varying Coefficient Models with Unknown Link and Variance Functions for Large-Scale Data. Statistica Sinica. 32, 847-868.

  3.  Jiakun Jiang, Huazhen Lin*, Qingzhi Zhong and Yi Li (2022). Analysis of multivariate non-gaussian functional data: a semiparametric latent process approach. Journal of Multivariate Analysis. 189,104888.

  4. Jiakun Jiang, Huazhen Lin*, Heng Peng, Gang-Zhi Fan, and Yi Li (2022). Cluster Analysis with Regression of Non-Gaussian Functional Data on Covariates. Canadian Journal of Statistics. 50,221-240.

  5. Zhou, L., Sun, S., Hu, H. and Song, P.X.K. (2022). Subgroup-effects models for the analysis of personal treatment effects. Annals of Applied Statistics 16(1): 80-103

  6. Yujia Wu., Lan, W., Zou, T and Tsai, C.-L 2022. Inward and outward network influence analysis, Journal of Business & Economic Statistics, 40:4, 1617-1628

  7. Lan,W., Chen, X*., Zou, T. and Tsai, C-L.(2022). Imputations for High Missing Rate Data in Covariates via Semi-supervised Learning Approach. Journal of Business and Economic Statistics , 40:3, 1282-1290

  8. Chen, X., Leung, H. and Qin, J.(2022) . Nonignorable missing data, single index propensity score and a profile synthetic distribution function method. Journal of Business and Economic Statistics , 40:2, 705-717

  9. Chang, J., Cheng, G. & Yao, Q. (2022). Testing for unit roots based on sample autocovariances, Biometrika, 109(2):543-550

  10. Li, Z., Liu, Y., & Lin, X. (2022). Simultaneous Detection of Signal Regions Using Quadratic Scan Statistics With Applications to Whole Genome Association Studies. Journal of the American Statistical Association, 117:538, 823-834.

  11. Xiang Wu, Liang Wu*, Shujuan Chen, 2022, Long memory and efficiency of Bitcoin during COVID-19. Applied Economics, , 54:4, 375-389

  12. Tao Liang, Wenya Wang, Fengmao Lv*. (2022) "Weakly-supervised domain adaption for aspect extraction via multi- level interaction transfer." IEEE Transactions on Neural Networks and Learning Systems (IEEE T-NNLS), 33(10):5818-5829.

  13. Long Feng., Wei Lan., Binghui Liu and Yanyuan Ma (2022). High-dimensional test for alpha in linear factor pricing models with sparse alternatives, Journal of Econometrics, 2291152-175

  14. Zou, T., Lan, W., Li, R and Tsai, C.-L 2022. Inferences on covariance-mean regression, Journal of Econometrics, 2302318-338 (共同一作)

  15. Jun Jin ,Tiefeng Ma,Jiajia Dai,Shuangzhe Liu. (2022). Penalized weighted composite quantile regression for partially linear varying coefficient models with missing covariates, Computational Statistics, 36.(1)541-575

  16. You, M., Lin, H., & Liang, H. (2022).Dynamically integrated regression model for online auction data. SCIENCE CHINA Mathematics. 66(7)1531-1552

  17. Liu, Y., Li, Z., & Lin, X. (2022). A Minimax Optimal Ridge-Type Set Test for Global Hypothesis with Applications in Whole Genome Sequencing Association Studies. Journal of the American Statistical Association, 117:538, 897-908.

  18. Shanghong Xie,Erin McDonnel,Yuanjia Wang2022Conditional Gaussian graphical model for estimating personalized disease symptom networksStatistics in Medicine 41:543–553.

  19. Xiaoqing Tan,Chung-Chou H. Chang, Ling Zhou, Lu TangA Tree-based Model Averaging Approach for Personalized Treatment Effect Estimation from Heterogeneous Data SourcesProceedings of the 39 th International Conference on Machine Learning, 162, 2022.

  20. Rui She, Zichuan Mi, Shiqing Ling. (2022) "Whittle parameter estimation for vector ARMA models with heavy-tailed noises" Journal of Statistical Planning and Inference 219:216–230

  21. Zhou, F., Fu,L., Li, Z. and Xu,J. (2022). The recurrence of financial distress: A survival analysis. International Journal of Forecasting,.38(3):1100-1115.

  22. Xiran Peng, Tao Zhu, Tong Wang, Fengjun Wang, Ke Li* and Xuechao Hao, (2022)"Machine learning prediction of postoperative major adverse cardiovascular events in geriatric patients: a prospective cohort study"  BMC Anesthesiology 22:284

  23. Wei Liu, Xu Liao, Yi Yang,Huazhen Lin, Joe Yeong, Xiang Zhou*, Xingjie Shi*, Jin Liu* (2022). Joint dimension reduction and clustering analysis of single-cell RNA-seq and spatial transcriptomics data. Nucleic Acids Research.50, e72.

  24. Shanghong Xie, Wenbo Wang, Qinxia Wang, Yuanjia Wang, Donglin Zeng(2022) Evaluating effectiveness of public health intervention strategies for mitigating COVID-19 pandemic.Stat Med ,41:3820–3836

  25. 姚潇,李可,余乐安(2022)非平衡样本下基于生成对抗网络过抽样技术的公司债券违约风险预测研究,系统工程理论与实践, 第42卷第10期2617-2643

  26. Ling Zhou & Peter X.-K. Song,2022, A discussion on “A selective review of statistical methods using calibration information from similar studies” Statistical Theory and Related Fields, 6:3, 196-198

  27. Zirui Sun#, Mingwei Dai#, Yao Wang, Shao-Bo Lin,2022, Nystrom Regularization for Time Series Forecasting*Journal of Machine Learning Research 23 , 1-42

  28. Fode Zhang; Jialiang Li; Hon Keung Tony Ng,2022,Minimum f-Divergence Estimation with Applications to Degradation Data Analysis,IEEE Transactions on Information Theory,68:10.1-1

  29. Xiao Bofei, Lei Bo, Lan Wei and Guo Bin,2022,A Blockwise Network Autoregressive Model with Application for Fraud Detection" Annals of the Institute of Statistical Mathematics,74, pages 1043–1065 

  30. Zhou Jing., Wei Lan and Hansheng Wang, " 2022,Asymptotic covariance estimation by Gaussian random perturbation,Computational Statistics & Data Analysis,Volume 171, 107459

  31. Linlin Dai, Kani Chen, Gang Li and Yuanyuan Lin,(2022).Metric Learning via Cross-Validation,Statistica Sinica,32, 1701-1721

  32. Rong Zhang, Jing Zhou, Wei Lan and Hansheng Wang (2022), A case study on the shareholder network effect of stock market data: An SARMA approach,Science China Mathematics, 65, pages 2219–2242



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