Student / Mentee author *, Corresponding author __
Zhou, Y.*, Yu, H. & Nordman, D. J. (2026+). Spectral empirical likelihood bootstrap inference with applications to weak ARMA models.
Han, X.*, Yu, H. & Yau, C. Y. (2026+). A simple spectral test for white noise.
Zhang, Q., Yu, H., Lahiri, S. N. & Nordman, D. J. (2026+). Nonparametric inference under long-memory time series.
Bera, S.*, Yu, H., Nordman, D. J. & Bandyopadhyay, S. (2026+). On the Bias of Spectral Estimators for Irregularly Spaced and Non-uniformly Sampled Spatial Data.
Yu, H. & Nordman, D. J. (2026+). New bootstrap inference framework: bridging subsampling and resampling.
Yu, H., Kaiser, M. S., & Nordman, D. J. (2025). A practical interval estimation for spectral density distribution. Journal of the American Statistical Association, 1–13. https://doi.org/10.1080/01621459.2025.2516211
Yu, H., Kaiser, M. S., & 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., & 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., & Yu. H. (2021). Optimal change-point estimation in time series. The Annals of Statistics, 49(4), 2336–2355. DOI: 10.1214/20-AOS2039 (alphabetical order)