Publications (Selected)

Selected Papers in Statistical Journals:

  1. Hanjia Gao and Xiaofeng Shao (2023+) Two sample testing in high dimension via Maximum Mean Discrepancy. Journal of Machine Learning Research, to appear. 2109.14913.pdf (arxiv.org)
  1. Daisuke Kurisu, Kengo Kato and Xiaofeng Shao (2023+) Gaussian approximation and spatially dependent wild bootstrap for high-dimensional spatial data. Journal of the American Statistical Association, to appear. [2103.10720]
  1. Runmin Wang and Xiaofeng Shao (2023) Dating the break in High Dimensional Data. Bernoulli, to appear. https://arxiv.org/abs/2002.04115

   1. Zifeng Zhao, Feiyu Jiang and Xiaofeng Shao (2022) Segmenting time series via self-normalization.   Journal of Royal Statistical Society, Series B, 84(5), 1699-1725.   https://arxiv.org/abs/2112.05331v1

  1. Runmin Wang*, Changbo Zhu*, Stanislav Volgushev, Xiaofeng Shao (2022) Inference for Change Points in High Dimensional Data via Self-Normalization. Annals of Statistics, 50(2), 781-806. (Wang* and Zhu* are joint first authors, equal contributions)

Link

  1. Feiyu Jiang, Zifeng Zhao and Xiaofeng Shao (2022) Modelling the COVID-19 infection trajectory: A piecewise linear quantile trend model. Journal of Royal Statistical Society, Series B, with discussion, 84(5), 1589-1607.

Link

  1. Yangfan Zhang, Runmin Wang and Xiaofeng Shao (2022) Adaptive inference for change-points in high-dimensional data. Journal of the American Statistical Association, 117, 1751-1762.

PDF

  1. Changbo Zhu and Xiaofeng Shao (2021) Interpoint Distance Based Two Sample Tests in High Dimension.
    Bernoulli, 27(2): 1189-1211.

PDF

  1. Xin Zhang, Chung Eun Lee and Xiaofeng Shao (2020) Envelopes in Multivariate Regression Models with Nonlinearity and Heteroscedasticity. Biometrika, 107(4), 965-981.

PDF

  1. Changbo Zhu, Xianyang Zhang, Shun Yao and Xiaofeng Shao (2020) Distance-based and RKHS-based Dependence Metrics in High Dimension.
    Annals of Statistics, 48(6), 3366-3394.
    PDF
  2. Runmin Wang and Xiaofeng Shao (2020) Hypothesis Testing for High-dimensional Time Series via Self-normalization. Annals of Statistics, 48(5), 2728-2758.
    PDF

R codes

  1. Chung Eun Lee, Xianyang Zhang and Xiaofeng Shao (2020) Testing the conditional mean independence of functional data. Biometrika, 107(2), 331-346. PDF

R codes

  1. Shun Yao, Xianyang Zhang and Xiaofeng Shao (2018) Testing mutual independence in high dimension via distance covariance. Journal of Royal Statistical Society, Series B, 80(3), 455-480. R codes

Link

  1. Xianyang Zhang, Shun Yao and Xiaofeng Shao (2018) Conditional mean and quantile dependence testing in high dimension. Annals of Statistics, 46(1), 219-246.

Link

  1. Chung Eun Lee and Xiaofeng Shao (2018) Martingale difference divergence matrix and its application to dimension reduction for stationary multivariate time series. Journal of the American Statistical Association, 113, 216-229.

Link

  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

R codes and data

  1. Xianyang Zhang and Xiaofeng Shao (2016) On the coverage bound problem of empirical likelihood methods for time series. Journal of Royal Statistical Society, Series B, 78, 395-421.

PDF

R codes and data

  1. Xiaofeng Shao (2015) Self-normalization for time series: a review of recent developments. Journal of the American Statistical Association, 110, 1797-1817.

PDF

  1. 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)

PDF and Supplementary material

  1. Xiaofeng Shao and Jingsi Zhang (2014) Martingale difference correlation and its use in high dimensional variable screening. Journal of the American Statistical Association, 109, 1302-1318. (with online supplementary material)

PDF and Supplementary material

  1. Xianyang Zhang and Xiaofeng Shao (2013) Fixed-smoothing asymptotics for time series. Annals of Statistics, 41, 1329-1349 (with online supplemental material)

PDF and Supplementary material

  1. Zhou Zhou and Xiaofeng Shao (2013) Inference for linear models with dependent errors. Journal of the Royal Statistical Society, Series, B., 75, 323-343.

PDF

  1. Xiaofeng Shao and Dimitris N. Politis (2013) Fixed-b subsampling and block bootstrap: improved confidence sets based on p-value calibration. Journal of the Royal Statistical Society, Series, B., 75, 161-184(Published version and Full Version)

PDF and PDF

  1. Xiaofeng Shao and Xianyang Zhang (2010) Testing for change points in time series. Journal of the American Statistical Association, 105, 1228-1240.

PDF Some R codes

  1. Xiaofeng Shao (2010) A self-normalized approach to confidence interval construction in time series. Journal of the Royal Statistical Society, Series, B. 72(3), 343-366. Corrigendum: 2010, 72(5), 695-696. arXiv version (with correction):

PDF

  1. Xiaofeng Shao (2010) The dependent wild bootstrap. Journal of the American Statistical Association. 105, 218-235.

PDF and Supplementary material

  1. Xiaofeng Shao (2009) Confidence intervals for spectral mean and ratio statistics. Biometrika. 96, 107-117.

PDF

  1. Xiaofeng Shao and Wei Biao Wu (2007) Asymptotic spectral theory for nonlinear time series. Annals of Statistics. 35(4), 1773-1801.

PDF

Selected Papers in Econometrics Journals:

  1. Jinyuan Chang, Qing Jiang and Xiaofeng Shao (2022) Testing the martingale difference hypothesis in high dimension. Journal of Econometrics, to appear. https://arxiv.org/abs/2209.04770?gathStatIcon=true
  1. Guochang Wang, Ke Zhu and Xiaofeng Shao (2022) Testing for the martingale difference hypothesis in multivariate time series models. Journal of the Business and Economic Statistics, 40(3), 980-994.

PDF

  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.

PDF

  1. 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, 80-92.

Link

  1. Yeonwoo Rho and Xiaofeng Shao (2019) Bootstrap-assisted unit root testing with piecewise locally stationary errors. Econometric Theory, 35, 142-166.

Link

  1. 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.

PDF

  1. Xiaofeng Shao (2011) A bootstrap-assisted spectral test of white noise under unknown dependence. Journal of Econometrics. 162, 213-224.

PDF

  1. Xiaofeng Shao (2011) Testing for white noise under unknown dependence and its applications to goodness-of-fit for time series models. Econometric Theory. 27, 312-343.

PDF

  1. Xiaofeng Shao (2010) Nonstationarity-extended Whittle Estimation. Econometric Theory. 26, 1060-1087.

PDF

  1. Xiaofeng Shao (2009) A generalized portmanteau test for independence between two stationary time series. Econometric Theory. 23(1), 195-210. (Published version and Full Version)

PDF and PDF

  1. Xiaofeng Shao and Wei Biao Wu (2007) Local Whittle estimation of fractional integration for nonlinear processes. Econometric Theory. 23, 899-929.

PDF

  1. Wei Biao Wu and Xiaofeng Shao (2007) A limit theorem for quadratic forms and its applications. Econometric Theory. 23, 930-951.

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Tjalling C. Koopmans Econometric Theory Prize for 2006-2008 PDF