Happy Wheels Krunkerigri Araba Oyunu
YAU, Chun Yip 邱俊業
Name YAU, Chun Yip 邱俊業
Title Director, Risk Management Science Program
Position Associate Professor
Email cyyau@sta.cuhk.edu.hk
Phone Number 3943 7942
Fax Number 2603 5188
Address LSB 110
Homepage http://www.sta.cuhk.edu.hk/CYYau/
Detail Image
Academic Background

B.Sc. (HKU) 2004

M.Phil. (CUHK) 2006

Ph.D. (Columbia) 2010

Research Interest
Time Series
Change-Point Analysis
Composite Likelihood Inference
Spatial Statistics
Environmental Statistics

Selected Publications
  1. Kwate, N.O.,  Yau, C.Y., Loh J.M., & Williams D. (2009). Inequality in obesigenic environments: fast food density in New York City, Health Place 15 (1), 364–373.
    --- Reprinted in Taking Food Public: Redfining Foodways in a Changing World. (2011). Editor: P.W. Forson, C. Counihan. Routledge, New York.
  2. Davis, R.A. & Yau, C.Y. (2011). Comments on pairwise likelihood in time series models. Statistica Sinica, 21(1), 255–278.
  3. Yau, C.Y. (2012). Empirical likelihood in long-memory time series models. Journal of Time Series Analysis, 33(2), 269–275.
  4. Loh, J.M. & Yau, C.Y. (2012). A generalization of Neyman-Scott process. Statistica Sinica, 22(4), 1717–1736. 
  5. Davis, R.A. & Yau, C.Y. (2012). Likelihood Inference for discriminating between long-range dependence and change-point models. Journal of Time Series Analysis, 33(4), 649–664.
  6. Davis, R.A. & Yau, C.Y. (2013). Consistency of minimum description length model selection for piecewise stationary times series models. Electronic Journal of Statistics, 7, 381–411.
  7. Chan, N.H., Yau, C.Y. & Zhang, R.M. (2014).  Group LASSO for structural break time series. Journal of the American Statistical Association, 109, 590–599.
  8. Yau, C.Y. (2014). Discussion on "Multiscale change point inference" by Frick, K., Munk, A. and Sieling, H. Journal of the Royal Statistical Society - Series B. 76, 565–566.
  9. Chan, N.H., Li, Z. & Yau, C.Y. (2014).  Forecasting online auctions via self‐ exciting point processes. Journal of Forecasting, 33(7), 501–514.
  10. Chan, N.H., Chen, K. & Yau, C.Y. (2014). On the Bartlett correction of empirical likelihood in Gaussian long-memory time series. Electronic Journal of  Statistics, 8, 1460–1490.
  11. Chan, N.H., Ng, C.T. & Yau, C.Y. (2014). Likelihood inferences for high dimensional dynamic factor analysis with applications in finance. Journal of Computational and Graphical Statistics, 24(3), 866–884.
  12. Chan, N.H., Yau, C.Y. & Zhang, R.M. (2014).  LASSO estimation of threshold autoregressive models. Journal of Econometrics, 189(2), 285–296.
  13. Lee, T.C.M., Tang, C.M. & Yau, C.Y. (2015). Estimation of multiple-regime threshold autoregressive models with structural breaks. Journal of the American  Statistical Association, 110, 1175–1186.
  14. Chan, K.W. & Yau, C.Y. (2016). New recursive estimators of the time-average variance constant. Statistics and Computing, 26, 609–627.
  15. Ma, T.F. & Yau, C.Y. (2016). A pairwise likelihood-based approach for change- point detection in multivariate time series models. Biometrika, 103(2), 409–421.
  16. Wu, C., Wang, M.H., Lu, X., Chong, K.C.,  He, J., Yau, C.Y., Hui, M., Cheng, X, Yang, L., Zee, B.C.Y., Zhang R., He, M.L. (2016) Concurrent epidemics of influenza A/H3N2 and A/H1N1pdm in Southern China: A serial cross-sectional study. Journal of Infection, 72, 369–376.
  17. Yau, C.Y. & Zhao Z. (2016). Inference for multiple change-points in time series via likelihood ratio scan statistics. Journal of the Royal Statistical Society - Series B, 78(4), 895–916.
  18. Chan, N.H., Wang, M. & Yau, C.Y. (2016). Nonlinear Error Correction Model and Multiple-threshold Cointegration. Statistica Sinica, 26(4), 1479–1499.
  19. Chan, N.H., Chen, K. & Yau, C.Y. (2016). Bartlett correction of empirical likelihood for non-Gaussian short memory time series. Journal of Time Series Analysis, 37(5), 624–649.
  20. Chan, N.H., Ing, C.K., Li, Y. & Yau, C.Y. (2017) Threshold Estimation via Group Orthogonal Greedy Algorithm. Journal of Business and Economic Statistics, 35(2), 334–345.
  21. Leung, S.H., Ng, W.L. & Yau, C.Y. (2017). Sequential change-point detection in time series models based on pairwise likelihood. Statistica Sinica, 27(2), 575–606.
  22. Ng, C.T. & Yau, C.Y. (2017). Selection of change-point models with Bayesian information criterion. Statistics and its interface, 10(2), 343–353.
  23. Hui, T.S. and Yau, C.Y. (2017) LARS-type algorithm for Group Lasso Estimation. Statistics and computing, 27(4), 1041–1048.
  24. Chan, N.H., Lu, Y. & Yau. C.Y. (2017). Factor Modeling for High-dimensional Time Series: Inference and Model Selection. Journal of Time Series Analysis, 38(2), 285–307.
  25. Chan, K.W. & Yau, C.Y. (2017). Automatic Optimal Batch Size Selection for Recursive Estimators of Time-average Covariance Matrix. Journal of the American Statistical Association, 112, 1076–1089.
  26. Chan, K.W. & Yau, C.Y. (2017). High order corrected estimator of time-average variance constant. Scandinavian Journal of Statistics, 44, 866–898.
  27. Gao, Q, Lee, T.C.M. & Yau, C.Y. (2017). Nonparametric Modeling and Break Point Detection for Time Series Signal of Counts. Signal Processing, 138, 307–312.
  28. Ng, W.L. & Yau, C.Y. (2018). Test for existence of finite moments via bootstrap. Journal of Nonparametric Statistics, 30(1), 28–48.
  29. Ng, W.L, Yau, C.Y. & Yip, T.C.F. (2018) A Hidden Markov Model for Earthquake Prediction. Stochastic Environmental Research and Risk Assessment, 32(5), 1415–1434. https://link.springer.com/article/10.1007/s00477-017-1457-1
  30. Chan, N.H., Chen, K., Huang, R. & Yau, C.Y., (2019) Subgroup Analysis of Zero- Inflated Poisson Regression Model with Application to Insurance Data. Insurance: Mathematics and Economics, 86, 8–18. https://doi.org/10.1016/j.insmatheco.2019.01.009
  31. Li, Y., Yau, C.Y. & Zheng, X (2019) Generalized threshold latent variable model. Electronic Journal of Statistics, 13(1), 2043–2092. https://projecteuclid.org/euclid.ejs/1561168838
  32. Chen, K, Chan, N.H., Wang, M. & Yau, C.Y. (2019) On Bartlett Correction of Empirical Likelihood for Regularly Spaced Spatial Data. Canadian Journal of Statistics, 47, 455–472. https://onlinelibrary.wiley.com/doi/10.1002/cjs.11508
  33. Chan, L.H., Chen, K., Li, C., Wong, C.W. & Yau, C.Y. (2019) On Higher Order Moment and Cumulant Estimation. Journal of Statistical Computation and Simulation, 90(4), 747–771. https://www.tandfonline.com/doi/full/10.1080/00949655.2019.1700987 
  34. Chan, N.H., Ling, S.Q., & Yau, C.Y. (2020) Lasso-based Variable Selection of ARMA Models. Statistica Sinica, 30, 1925-1948. doi:10.5705/ss.202017.0500 
  35. Chen, K, Chan, N.H. & Yau, C.Y. (2020) Bartlett Correction of Empirical Likelihood with Unknown Variance. Annals of Institute of Statistical Mathematics, 72, 1159–1173. https://doi.org/10.1007/s10463-019-00723-5 
  36. Chan, N.H., Li, Y., Yau, C.Y. and Zhang, R (2021) Group Orthogonal Greedy Algorithm for Change-point Estimation of Multivariate Time Series. Journal of Statistical Planning and Inference, 212, 14–33. https://doi.org/10.1016/j.jspi.2020.08.002 
  37. Chan, N.H., Ng, W.L. & Yau, C.Y. (2021) A Self-Normalized Approach to Sequential Change-point Detection for Time Series. To appear in Statistica Sinica.
  38. Yau, C.Y., Zhu, Z, Loh, J.M. & Lai, S.Y. (2021) Spatial Sampling Design using Generalized Neyman-Scott Process. To appear in Journal of Agricultural, Biological and Environmental Statistics 
  39. Yau, C.Y. (2021) Factor Modeling for High Dimensional Time Series. To appear in Handbook of Computational Statistics and Data Science.  
  40. Liu, Z. & Yau, C.Y. (2021) Time Series Analysis for Longitudinal Survey Data Under Informative Sampling and Nonignorable Missingness. To appear in REVSTAT
  41. Chan, N.H., Ng, W.L, Yau, C.Y., Yu, H. (2021) Optimal Change-point Estimation in Time Series. To appear in Annals of Statistics.
  42. Ng, W.L, Pan, S. & Yau, C.Y. (2021+) Bootstrap Inference for Multiple Change-points in Time Series. (Submitted)
  43. Liu, Z. & Yau, C.Y. (2021+) Fitting time series models for longitudinal surveys with nonignorable missing data. (Submitted) 
  44. Yau, C.Y. & Zhao, Z. (2021+) Alternating Dynamic Programming for Multiple Epidemic Change-Point Estimation. (Submitted) 
  45. Zhao, Z., Ma, T.F., Ng, W.L. & Yau, C.Y. (2021+) A Composite Likelihood-based Approach for Change-point Detection in Spatio-temporal Process. (Submitted) 
  46. Chan, K.W. & Yau, C.Y. (2021+). Asymptotically Constant Risk Estimator of Time-average Variance Constant. (Submitted)  
  47. Liu, Z. & Yau, C.Y. (2021+) A propensity score adjustment method for longitudinal time series models under nonignorable nonresponse. (Submitted) 
  48. Li, Y., Ng, C.T., & Yau, C.Y. (2021+) GARCH-Type factor model. (Submitted) 
  49. Chen, X, Ng, W.L. & Yau, C.Y. (2021+) Frequency Domain Bootstrap Methods for Spatial Lattice Data. (Submitted) 
  50. Ng, W.L. & Yau, C.Y. (2021+) Asymptotic Spectral Theory for Spatial Data. (Submitted)  
  51. Chen, K., Chan, N.H, Yau, C.Y. and Hu, J. (2021+) Penalized Whittle Likelihood for massive spatial data. (Submitted) 

RMSC1101 Elementary Concepts in Risk Management
RMSC4005 Stochastic Calculus for Finance and Risk
STAT3008 Applied Regression Analysis
STAT4005 Time Series
STAT6104 Financial Time Series

RMSC Program Orientation 2018 (pdf)

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