Students

    (with their placements and select publications)

  • (2010) Zhewen Fan, Ph.D. (joint with Jeff Douglas). “Statistical Issues and Developments in Time Series Analysis and Educational
    Measurements.” Current job: Quantitative Analyst at PNC.
  • (2013) Xianyang Zhang , Ph.D. “Statistical Inference for Dependent Data.” Current job: Associate Professor, Texas A&M University, Department of Statistics.
    1. Xianyang Zhang and Xiaofeng Shao (2013) Fixed-smoothing asymptotics for time series. Annals of Statistics, 41, 1329-1349 (with online supplemental material)
    2. PDF and Supplementary material

    3. Xianyang Zhang and Xiaofeng Shao (2015) Two sample inference for the second-order property of temporally dependent functional data. Bernoulli, 21, 909-929. (with online supplementary material)
    4. PDF and Supplementary material

  • (2014) Yeonwoo Rho , Ph.D. “Inference of Time Series Regression Models with Weakly Dependent Errors .” Current job: Associate Professor, Michigan Technological University, Department of Mathematical Sciences.
    1. Yeonwoo Rho and Xiaofeng Shao (2018) Bootstrap-assisted unit root testing with piecewise locally stationary errors. Econometric Theory, to appear.
    2. Link

    3. Yeonwoo Rho and Xiaofeng Shao (2015) Inference for time series regression models with weakly dependent and heteroscedastic errors. Journal of Business and Economic Statistics, 33, 444-457.
    4. PDF

  • (2016) Srijan Sengupta , Ph.D. (Joint with Yuguo Chen)“ Statistical Analysis of Networks With Community Structure And Bootstrap Methods For Big Data.” Current job: Assistant Professor, North Carolina State University, Department of Statistics, 2020-present
    1. Srijan Sengupta, Stanislav Volgushev, and Xiaofeng Shao (2016) A subsampled double bootstrap for massive data. Journal of the American
      Statistical Association, 111, 1222-1232. PDF
    2. R codes and data

  • (2017) Chung Eun Lee, Ph.D. student.”Statistical Inference of Multivariate Time Series and Functional Data Using New Nonlinear Dependence Metrics.” Current job: Assistant Professor, University of Tennessee, Department of Business Analytics and Statistics (Aug 2017-present)
    1. Chung Eun Lee and Xiaofeng Shao (2017) Martingale difference divergence matrix and its application to dimension reduction for stationary multivariate time series. Journal of the American Statistical Association, to appear.
    2. Link

    3. Chung Eun Lee and Xiaofeng Shao (2020) Volatility Martingale Difference Divergence Matrix and Its Application to Dimension Reduction for Multivariate Volatility. Journal of Business and Economic Statistics, 38(1), 80-92..
    4. Chung Eun Lee, Xianyang Zhang and Xiaofeng Shao (2020) Testing the conditional mean independence of functional data. Biometrika, to appear.
  • (2017) Shun Yao, Ph.D. student. (with Xianyang Zhang at Texas A&M) “Dependence Testing in High Dimension.” Current Job: Quantitative Analyst, Goldman Sachs at New York City (Aug 2017-present)
    1. Shun Yao, Xianyang Zhang and Xiaofeng Shao (2017) Testing mutual independence in high dimension via distance covariance. Journal of Royal Statistical Society, Series B, to appear. R codes
    2. Link

  • (2020) Runmin Wang, Ph.D. student. “Statistical Inference for High-dimensional Data via U-statistics.” Current Job: Assistant Professor, Southern Methodist University, Department of Statistical Sciences (July 2020-present)
    1. Runmin Wang and Xiaofeng Shao (2020+) Hypothesis Testing for High-dimensional Time Series via Self-normalization. Annals of Statistics, to appear.
    2. Runmin Wang*, Changbo Zhu*, Stanislav Volgushev, Xiaofeng Shao (2021) Inference for Change Points in High Dimensional Data via Self-Normalization. Annals of Statistics, to appear. (Wang* and Zhu* are joint first authors, equal contributions)
    3. Link

  • (2020) Changbo Zhu, Ph.D. student. “Statistical Inference for High-dimensional Data.” Current Job: Postdoc Fellow, University of California, Davis, Department of Statistics (Fall 2020-present)
    1. Changbo Zhu, Xianyang Zhang, Shun Yao and Xiaofeng Shao (2020+) Distance-based and RKHS-based Dependence Metrics in High Dimension.
      Annals of Statistics, to appear
    2. Changbo Zhu and Xiaofeng Shao (2020+) Interpoint Distance Based Two Sample Tests in High Dimension.
      Bernoulli, to appear.
    3. PDF

    4. Runmin Wang*, Changbo Zhu*, Stanislav Volgushev, Xiaofeng Shao (2021) Inference for Change Points in High Dimensional Data via Self-Normalization. Annals of Statistics, to appear. (Wang* and Zhu* are joint first authors, equal contributions)
    5. Link

  • (2021) Teng Wu, Ph.D. student. (with Naveen Narisetty) “Change point detection for high dimensional data and valid inference for Bayesian linear models.” Current Job: Data Scientist, Microsoft (July 2021-present)
    1. Teng Wu, Runmin Wang, Hao Yan and Xiaofeng Shao (2021) Adaptive change-point monitoring for high-dimensional data. Statistica Sinica, to appear.
    2. PDF

  • (2021) Feiyu Jiang, visiting Ph.D. student from Tsinghua University. (Aug 2019-Aug 2020) “Change point analysis for COVID-19 time series.” Current Job: Assistant Professor, School of Management, Fudan University, (July 2021-present)
    1. Feiyu Jiang, Zifeng Zhao and Xiaofeng Shao (2021) Time Series Analysis of COVID-19 infection curve: a change-point perspective. Journal of Econometrics, to appear.
    2. PDF

    3. Feiyu Jiang, Zifeng Zhao and Xiaofeng Shao (2021) Modelling the COVID-19 infection trajectory: A piecewise linear quantile trend model. Journal of Royal Statistical Society, Series B, with discussion, to appear.
    4. Link