Publication

Wang, R. and Shao, X. (2021+). Dating the Break in High Dimensional Data. Under review. (https://arxiv.org/pdf/2002.04115.pdf)

Mai, Q., Shao, X., Wang, R. and Zhang, X. (alphabetical order, equal contribution) (2021+). Slicing-free High-Dimensional Sufficient Dimension Reduction with the Martingale Difference Divergence Matrix. Under review.

Jiang, F., Wang, R.* and Shao, X. (*corresponding author) (2022). Robust Inference for Change Points in High-Dimension Data. Journal of Multivariate Analysis, to appear.

Wang, R.*, Zhu, C.* (joint first author), Volgushev, S. and Shao, X. (2021). Inference for Change Points in High-Dimensional Data via Self-Normalization. The Annals of Statistics, 50(2), 781-806.

Zhang, Y., Wang, R. and Shao, X. (2021). Adaptive Inference for Change Points in High-Dimensional Data. Journal of the American Statistical Association, pp. 1-12.

Wu, T., Wang, R., Yan, H. and Shao, X. (2021). Adaptive Change Point Monitoring for High-Dimensional Data. Statistica Sinica, to appear.

Wang, R. and Shao, X. (2020). Hypothesis Testing for high-dimensional time series via self-normalization. The Annals of Statistics, 48(5), 2728-2758.