Dr NG Wai Leong, Tom (吳偉亮博士)
B.Sc. (CUHK)
M.Phil. (CUHK)
Ph.D. (CUHK)

Assistant Professor
Department of Mathematics, Statistics and Insurance
BSC-DSBI Associate Programme Director

電話 : (852) 3963 5666
電郵 :
wlng@hsu.edu.hk


Dr Ng received his B.Sc. in Risk Management Science, M.Phil. in Risk Management Science, and Ph.D. in Statistics from the Department of Statistics at The Chinese University of Hong Kong.

Research InterestsPublicationsResearch Grants
TopResearch Interests

  • Change-point Analysis

  • Bootstrap Resampling Method

  • Time Series

TopPublications

..........Journal Articles..........




  1. Ng, W. L., Yau, C. Y. and Chen, X. (2021). Frequency Domain Bootstrap Methods for Random Fields. Electronic Journal of Statistics, 15(2), 6586-6632. DOI: 10.1214/21-EJS1959

  2. Chan, N. H., Ng, W. L., Yau, C. Y. and Yu, H. (2021). Optimal Change-point Estimation in Time Series. Annals of Statistics, 49(4), 2336-2355. DOI: 10.1214/20-AOS2039

  3. Chan, N. H., Ng, W. L., and Yau, C. Y. (2021). A Self-Normalized Approach to Sequential Change-point Detection for Time Series. Statistica Sinica, 31(1), 491-517. DOI: 10.5705/ss.202018.0269

  4. Ng, W. L.and Yau, C. Y. (2018). Test for Existence of Finite Moments via Bootstrap. Journal of Nonparametric Statistics, 30(1), 28-48.

  5. Yip, T. C. F., Ng, W. L.and Yau, C. Y. (2018). A Hidden Markov Model for Earthquake Prediction. Stochastic Environmental Research and Risk Assessment, 32, 1415-1434.

  6. Leung, S.H., Ng, W.L. and Yau, C.Y. (2017). Sequential Change-point Detection in Time Series Models based on Pairwise Likelihood. Statistica Sinica, 27(2), 575-606.

  7. Ng, W.L. and Yau, C.Y. (2018). Test for Existence of Finite Moments via Bootstrap. Journal of Nonparametric Statistics, 30(1), 28-48.

  8. Yip, T.C.F., Ng, W.L. and Yau, C.Y. (2018). A Hidden Markov Model for Earthquake Prediction. Stochastic Environmental Research and Risk Assessment, 32, 1415-1434.


TopResearch Grants

  1. (UGC/FDS14/P04/21) HK$973,000. “Sequential Change-Point Detection in High-Dimensional Vector Autoregressive Models” funded by the University Grants Committee (UGC) 2021/2022. (PI)

  2. (UGC/FDS14/P01/20) HK$1,628,450 “Inference for Multiple Change-points in Piecewise Locally Stationary Time Series,” funded by the University Grants Committee (UGC) 2020/2021. (PI)