Professor Bing-Yi JING (荆炳义)

Ph.D., University of Sydney (1993).


Research Interests:   

         Machine Learning & Data Mining
         Network Data Analysis
         Financial Econometrics
         Probability and Statistics

Associate Editors:    

          Journal of Business & Economic Statistics,   2012-present
          Canadian Journal of Statistics,                       2010-present
          Statistics and Its Interface,                             2010-present
          Science in China,                                            2012-present                     
          Journal of Data Analysis,                               2008-present     
          Statistical Theory and Related Fields,            2017-present

Other Position:

       Director: The Center for Statistical Science, 2012-present     

Selected Publications:    

         1. Jing, B.Y., Li, Z.P., Pan, G.M., Zhou W. (2016). 
             On SURE-type double shrinkage estimation. 
             To appear in Journal of the American Statistical Association.

         2. Guo, J.H., Hu, J.C., Jing, B.Y. and Zhang, Z. (2016). 
             Spline-Lasso in high-dimensional linear regression.
             Journal of the American Statistical Association, 111:513, 288-297.

         3. Kong, X.B., Liu, Z., and Jing, B.-Y. (2015). 
             Testing for pure-jump processes for high-frequency data. 
             Annals of Statistics 43(2), 847-877.

         4. Liu, Z., Abbas, A., Jing, B.-Y.*, Gao, X.* (2012).      [* Joint corresponding author]
             WaVPeak: picking NMR peaks through wavelet transform and volume-based filtering.  
             Bioinformatics, 28(7), 914-920. 

         5. Jing, B.-Y., Kong, X.B., Liu, Z. (2012). 
             Modeling high frequency data by pure jump processes.
             Annals of Statistics, 40(2), 759-784.

         6. Jing, B.-Y., Kong, X.B., Liu, Z., and Mykland, P. (2012).  
             On the jump activity index for semi-martingales. 
             Journal of Econometrics, 166, 213-223.

         7. Jing, B.-Y., Kong, X.B., Liu, Z. (2011). 
             Estimating the jump activity index of Levy processes under noisy observations using high frequency data. 
             Journal of the American Statistical Association, 106, 558-568.

         8. Jing, B.-Y., Pan, G.M., Shao, Q.M., Zhou, W. (2010). 
             Nonparametric estimate of spectral density functions of random matrices. 
             Annals of Statistics, 38, 3724-3750.

         9. Bentkus, V., Jing, B.-Y., and Zhou, W. (2009). 
             On normal approximations to U-statistics. 
             Annals of Probability, 37, 2174-2199.

        10. Jing, B.-Y., Yuan, J.Q. and Zhou, W. (2009). 
              Jackknife empirical likelihood. 
              Journal of the American Statistical Association, 104, 1124-1232.

        11. Jing, B.-Y., Shao, Q.M. and Zhou, W. (2004). 
              Saddlepoint approximation for Student's t-statistic with no moment conditions. 
              Annals of Statistics, 32, 2679{2711.

        12. Jing, B.-Y., Shao, Q.-M. and Wang, Q.Y. (2003). 
              Self-normalized Cramer-type large deviations for independent random variables. 
              Annals of Probability, 31, 2167-2215.

        13. Jing, B.-Y. and Wang, Q.Y. (2003). 
              Edgeworth expansions for U-statistics under minimal conditions. 
              Annals of Statistics, 31, 1376-1391.

        14. Wang, Q.Y. and Jing, B.-Y. (1999). 
              An exponential non-uniform Berry-Esseen bound for self-normalized sums. 
              Annals of Probability, 27, 2068-2088.

        15. Fisher, N., Hall, P., Jing, B.-Y. and Wood, A. (1996). 
              Improved pivotal methods for constructing confidence regions with directional data. 
              Journal of the American Statistical Association, 91, 1062-1070.

        16. Hall, P. and Jing, B.-Y. (1996). 
              On sample re-use methods for dependent data. 
              Journal of Royal Statistical Society, Series B, 58, 727-737.

        17. Jing, B.-Y. and Wood, A. (1996). 
              Exponential empirical likelihood is not Bartlett correctable.
              Annals of Statistics, 24, 365-369.

        18. Hall, P., Horowitz, J. and Jing, B.-Y. (1995). 
              On blocking rules for the bootstrap and dependent data. 
              Biometrika, 82, 561-74.

        19. Hall, P. and Jing, B.-Y. (1995). 
              Uniform coverage bounds for conŻdence intervals and Berry-Esseen theorems for Edgeworth expansion. 
              Annals of Statistics, 23, 363-375.

        20. Jing, B.-Y., Feuerverger, A. and Robinson, J. (1994). 
              On the bootstrap saddlepoint approximations. 
              Biometrika, 81, 211-215.

        21. Jing, B.-Y. and Robinson, J. (1994). 
              Saddlepoint approximations for marginal and conditional probabilities of transformed variables. 
              Annals of Statistics 22, 1115-1132. 1. 

Contact Information:

       Department of Mathematics
       Hong Kong University of Science & Technology
       Clear Water Bay, Kowloon
       Hong Kong.
       Phone:   (852) 2358 7458 (O).