Haihan (Mark) Yu

Haihan Yu
  • Assistant Professor | Director of Undergraduate Studies
  • Resampling methods, Dependent data, Model assessment
  • Email: haihan.yu@uri.edu
  • Office Location: Tyler 137
  • Website

Research

My current research focuses on non-parametric inference tools, bootstrap (resampling, subsampling), and empirical likelihood. My goal is to develop user-friendly as well as theoretically compact statistical methods. Besides non-parametric inference, I also have a broad interest in other statistical problems, including time series, change-point problems, model assessment, etc.

Education

2023 Ph.D. Iowa State University Statistics
2017 M.Phil. The Chinese University of Hong Kong Risk Management Science
2015 B.Sc. The Chinese University of Hong Kong Risk Management Science

Selected Publications

Yu, H., Kaiser, M. S., and Nordman, D. J. (2025). A practical interval estimation for spectral density distribution. Journal of the American Statistical Association (Theory and Methods), 338- 350. https://doi.org/10.1080/01621459.2025.2516211

Yu, H., Kaiser, M. S., and Nordman, D. J. (2024). A blockwise empirical likelihood method for time series in frequency domain inference. The Annals of Statistics, 52(3), 1152-1177. DOI: 10.1214/24-AOS2388

Yu, H., Kaiser, M. S., and Nordman, D. J. (2023). A subsampling perspective for extending the validity of state-of-the-art bootstraps in the frequency domain. Biometrika, 110(4) 1099–1115. https://doi.org/10.1093/biomet/asad006

Chan, N.H., Ng, W. L., Yau, C. Y., and Yu. H. (2021). Optimal change-point estimation in time series. The Annals of Statistics, 49(4), DOI: 10.1214/20-AOS2039