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师资团队Faculty

师资团队Faculty

代文林

职称:副教授、博士生导师(统计与大数据研究院)

研究方向:非参数统计;函数型数据、网络数据、时空数据分析与应用

联系方式:wenlin.dai@ruc.edu.cn

代文林博士2018年加入中国人民大学统计与大数据研究院,现为副教授、博士生导师。此前,他曾在沙特阿卜杜拉国王科技大学(KAUST)进行博士后研究,2014年于香港浸会大学获得统计学博士学位,2008年于北京理工大学获得统计学学士学位。研究兴趣包括非参数统计、函数型数据探索性分析、网络数据与时空数据分析及统计模型在环境、工业、经济等领域的应用。


个人主页:https://sites.google.com/view/wenlindai


Selected Publications


Functional Data Analysis

Maoyu Zhang#, Yan Songand Wenlin Dai* (2023), “Fast robust location and scatter estimation: a depth-based method”. Accepted by Technometrics.

Zhuo Qu#, Wenlin Dai and Marc G. Genton (2023), “Robust Two-Layer Partition Clustering of Sparse Multivariate Functional Data”. Accepted by Econometrics and Statistics.

Zhuo Qu#, Wenlin Dai* and Marc G. Genton (2021), “Robust functional multivariate analysis of variance with environmental applications”. Environmetrics, e2641.

Zonghui Yao#, Wenlin Dai* and Marc G. Genton (2020), “Trajectory functional boxplots”. Stat, e289.

Wenlin Dai, Tomas Mrkvicka, Ying Sun and Marc G. Genton (2020), “Functional outlier detection and taxonomy by sequential transformations”. Computational Statistics & Data Analysis, 106960.

Wenlin Dai and Marc G. Genton (2019), “Directional outlyingness for multivariate functional data”. Computational Statistics & Data Analysis, 131:50-65.

Wenlin Dai and Marc G. Genton (2018), “Multivariate functional data visualization and outlier detection”. Journal of Computational and Graphical Statistics, 27: 923-934.

Wenlin Dai and Marc G. Genton (2018), “An outlyingness matrix for multivariate functional data classification”. Statistica Sinica, 28: 2435-2454.


Nonparametric Regression

Maoyu Zhangand Wenlin Dai*, “Gradient estimation of multivariate nonparametric regression”. Accepted by Statistical Analysis and Data Mining.

Wenlin Dai, Xingwei Tong and Tiejun Tong, “Optimal-k difference sequence for variance estimation in nonparametric regression”. Under review.

Wenlin Dai, Tiejun Tong and Lixing Zhu (2017), “On the choice of difference sequence in a unified framework for variance estimation in nonparametric regression”. Statistical Science, 32: 455-468.

Wenlin Dai, Tiejun Tong and Marc G. Genton (2016), “Optimal estimation of derivatives in nonparametric regression”. Journal of Machine Learning Research, 17: 1–25.

Wenlin Dai, Yanyuan Ma, Tiejun Tong and Lixing Zhu (2015), “Difference-based variance estimation in nonparametric regression with repeated measurement data”. Journal of Statistical Planning and Inference, 163: 1–20.


Network Data Analysis

Maoyu Zhang#, Biao Cai, Wenlin Dai, Dehan Kong, Hongyu Zhao and Jingfei Zhang,“Learning Brain Connectivity in Social Cognition with Dynamic Network Regression”. In revision for Annals of Applied Statistics.

Haosheng Shi# and Wenlin Dai*, A community Hawkes model for continuous-time networks with interaction heterogeneity, Revised for Statistica Sinica.

Maoyu Zhang#, Jingfei Zhang and Wenlin Dai*, Modularity-based community detection for dynamic heterogeneous networks. Accepted by Journal of Computational and Graphical Statistics.

Maoyu Zhang#, Linsui Dengand Wenlin Dai*, Multiplex depth for network-valued data and applications. Revised for Journal of Computational and Graphical Statistics.


Data Reduction

Wenlin Dai, Yan Song# and Dianpeng Wang (2023), “A subsampling method for regression problems based on minimum energy criterion”. Technometircs, 65:2, 192-205.

Yan Song# and Wenlin Dai (2022), “Deterministic subsampling for logistic regression with massive data”. Accepted by Computational Statistics.

Yan Song#, Wenlin Dai* and Marc G. Genton. “Large-scale low-rank Gaussian process prediction with support points”. In revision for Journal of the American Statistical Association.


#: Supervised Student   *: Corresponding Author