Working Papers #
- Yi He and Bo Zhang, ``Testing for Spurious Factor Analysis on High Dimensional Nonstationary Time Series’’
Old title: ``Detecting Spurious Factor Models’’.
Presented at The 13th International Conference on Extreme Value Analysis, and seminars at University of Amsterdam, Chinese University of Hong Kong, University of Groningen, Singapore Management University, and Nanyang Technological University.
New Version at SSRN Old Version at FigShare Old Version at SSRNYi He and John H.J. Einmahl, ``Extreme Value Inference to General Heterogeneous Data’’.
Presented at Fens, Forests, Formulas workshop in Statistics and Probability (by Yi), 16th CMStatistics 2023 Conference at Berlin (by John), One World Extreme Seminar (by John).
Available at SSRNProfessor Laurens de Haan: Weer een stap voorwaarts in de ontwikkeling van EVT (English: Another step forward in the development of EVT.)
- Xuan Leng, Yi He, Yanxi Hou, Liang Peng, ``Asymptotics of CoVaR Inference In Two-Quantile-Regression’’.
- Yi He, Liang Peng, Dabao Zhang and Zifeng Zhao, ``Refining Kaplan-Meier Estimation with the Generalized Pareto Model for Survival Analysis’’.
Yi He and Juan-Juan Cai, ``Distribution Regression Approach for Cumulative Probability Models’’.
Presented at International Symposium on Nonparametric Statistics 2024
Yi He, Jia Li and Yuhong Zhu, ``Uniform Fixed-k Inference for Explosive Drift’’.
Yi He, Yongmiao Hong, Xuan Leng, and Yizhou Zhang, ``Inferring Quantile Treatment Effects using Extreme Value Theory’’.
Yi He and Tiandong Wang, ``Detecting Communities in Latent Networks’’
Yi He and Jiti Gao, ``Testing Against High-Dimensional Alternatives with Heteroskedasticity’’.
John H.J. Einmahl, and Yi He, ``Ultimate Athlete Records Are More Accurate Than You Think’’.
Hao Li, Tiandong Wang and Yi He, ``$P$-hacking and Network Centrality’’.
Yi He, Lina Zhang, and Xueyan Zhao, ``Improving Testing Power for Instrumental Variables Regression: A Semi-supervised Learning Approach’’
Yi He and Lingwei Kong, ``Taming the Factor Zoo Using Stability Selection’’.