Ph.D., University of Sydney (1993).
Machine Learning & Data Mining
Network Data Analysis
Financial Econometrics
Bioinformatics
Probability and Statistics
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.