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Xiaofeng Shao

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First Name:Xiaofeng
Middle Name:
Last Name:Shao
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RePEc Short-ID:psh274
[This author has chosen not to make the email address public]
http://publish.illinois.edu/xshao/

Research output

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Jump to: Working papers Articles

Working papers

  1. Jinyuan Chang & Qing Jiang & Xiaofeng Shao, 2022. "Testing the martingale difference hypothesis in high dimension," Papers 2209.04770, arXiv.org, revised Sep 2022.
  2. Feiyu Jiang & Zifeng Zhao & Xiaofeng Shao, 2020. "Time Series Analysis of COVID-19 Infection Curve: A Change-Point Perspective," Papers 2007.04553, arXiv.org.
  3. Yeonwoo Rho & Xiaofeng Shao, 2018. "Bootstrap-Assisted Unit Root Testing With Piecewise Locally Stationary Errors," Papers 1802.05333, arXiv.org.

Articles

  1. Jiang, Feiyu & Wang, Runmin & Shao, Xiaofeng, 2023. "Robust inference for change points in high dimension," Journal of Multivariate Analysis, Elsevier, vol. 193(C).
  2. Chang, Jinyuan & Jiang, Qing & Shao, Xiaofeng, 2023. "Testing the martingale difference hypothesis in high dimension," Journal of Econometrics, Elsevier, vol. 235(2), pages 972-1000.
  3. Jiang, Feiyu & Zhao, Zifeng & Shao, Xiaofeng, 2023. "Time series analysis of COVID-19 infection curve: A change-point perspective," Journal of Econometrics, Elsevier, vol. 232(1), pages 1-17.
  4. Feiyu Jiang & Zifeng Zhao & Xiaofeng Shao, 2022. "Modelling the COVID‐19 infection trajectory: A piecewise linear quantile trend model," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 84(5), pages 1589-1607, November.
  5. Yangfan Zhang & Runmin Wang & Xiaofeng Shao, 2022. "Adaptive Inference for Change Points in High-Dimensional Data," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 117(540), pages 1751-1762, October.
  6. Zifeng Zhao & Feiyu Jiang & Xiaofeng Shao, 2022. "Segmenting time series via self‐normalisation," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 84(5), pages 1699-1725, November.
  7. Feiyu Jiang & Zifeng Zhao & Xiaofeng Shao, 2022. "Jiang, Zhao and Shao's reply to the Discussion of ‘The First Discussion Meeting on Statistical Aspects of the Covid‐19 Pandemic’," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 185(4), pages 1849-1854, October.
  8. Guochang Wang & Ke Zhu & Xiaofeng Shao, 2022. "Testing for the Martingale Difference Hypothesis in Multivariate Time Series Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 40(3), pages 980-994, June.
  9. Chung Eun Lee & Xiaofeng Shao, 2020. "Volatility Martingale Difference Divergence Matrix and Its Application to Dimension Reduction for Multivariate Volatility," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 38(1), pages 80-92, January.
  10. C E Lee & X Zhang & X Shao, 2020. "Testing conditional mean independence for functional data," Biometrika, Biometrika Trust, vol. 107(2), pages 331-346.
  11. Rho, Yeonwoo & Shao, Xiaofeng, 2019. "Bootstrap-Assisted Unit Root Testing With Piecewise Locally Stationary Errors," Econometric Theory, Cambridge University Press, vol. 35(1), pages 142-166, February.
  12. Chung Eun Lee & Xiaofeng Shao, 2018. "Martingale Difference Divergence Matrix and Its Application to Dimension Reduction for Stationary Multivariate Time Series," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 113(521), pages 216-229, January.
  13. Shun Yao & Xianyang Zhang & Xiaofeng Shao, 2018. "Testing mutual independence in high dimension via distance covariance," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 80(3), pages 455-480, June.
  14. Xianyang Zhang & Xiaofeng Shao, 2016. "On the coverage bound problem of empirical likelihood methods for time series," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 78(2), pages 395-421, March.
  15. Srijan Sengupta & Stanislav Volgushev & Xiaofeng Shao, 2016. "A Subsampled Double Bootstrap for Massive Data," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 111(515), pages 1222-1232, July.
  16. Yeonwoo Rho & Xiaofeng Shao, 2015. "Inference for Time Series Regression Models With Weakly Dependent and Heteroscedastic Errors," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 33(3), pages 444-457, July.
  17. Xiaofeng Shao, 2015. "Self-Normalization for Time Series: A Review of Recent Developments," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 110(512), pages 1797-1817, December.
  18. Kim, Seonjin & Zhao, Zhibiao & Shao, Xiaofeng, 2015. "Nonparametric functional central limit theorem for time series regression with application to self-normalized confidence interval," Journal of Multivariate Analysis, Elsevier, vol. 133(C), pages 277-290.
  19. Yinxiao Huang & Stanislav Volgushev & Xiaofeng Shao, 2015. "On Self-Normalization For Censored Dependent Data," Journal of Time Series Analysis, Wiley Blackwell, vol. 36(1), pages 109-124, January.
  20. Giuseppe Cavaliere & Dimitris N. Politis & Anders Rahbek & Srijan Sengupta & Xiaofeng Shao & Yingchuan Wang, 2015. "Recent developments in bootstrap methods for dependent data," Journal of Time Series Analysis, Wiley Blackwell, vol. 36(3), pages 315-326, May.
  21. Xiaofeng Shao & Jingsi Zhang, 2014. "Martingale Difference Correlation and Its Use in High-Dimensional Variable Screening," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 109(507), pages 1302-1318, September.
  22. Xianyang Zhang & Bo Li & Xiaofeng Shao, 2014. "Self-normalization for Spatial Data," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 41(2), pages 311-324, June.
  23. Zhang, Jingsi & Jiang, Wenxin & Shao, Xiaofeng, 2013. "Bayesian model selection based on parameter estimates from subsamples," Statistics & Probability Letters, Elsevier, vol. 83(4), pages 979-986.
  24. Xiaofeng Shao & Dimitris N. Politis, 2013. "Fixed b subsampling and the block bootstrap: improved confidence sets based on p-value calibration," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 75(1), pages 161-184, January.
  25. Zhang, Xianyang & Shao, Xiaofeng, 2013. "On a general class of long run variance estimators," Economics Letters, Elsevier, vol. 120(3), pages 437-441.
  26. Zhou Zhou & Xiaofeng Shao, 2013. "Inference for linear models with dependent errors," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 75(2), pages 323-343, March.
  27. Xiaofeng Shao, 2012. "Parametric Inference in Stationary Time Series Models with Dependent Errors," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 39(4), pages 772-783, December.
  28. Xiaofeng Shao, 2011. "A simple test of changes in mean in the possible presence of long‐range dependence," Journal of Time Series Analysis, Wiley Blackwell, vol. 32(6), pages 598-606, November.
  29. Shao, Xiaofeng, 2011. "Testing For White Noise Under Unknown Dependence And Its Applications To Diagnostic Checking For Time Series Models," Econometric Theory, Cambridge University Press, vol. 27(2), pages 312-343, April.
  30. Shao, Xiaofeng, 2011. "A bootstrap-assisted spectral test of white noise under unknown dependence," Journal of Econometrics, Elsevier, vol. 162(2), pages 213-224, June.
  31. Shao, Xiaofeng, 2010. "Nonstationarity-Extended Whittle Estimation," Econometric Theory, Cambridge University Press, vol. 26(4), pages 1060-1087, August.
  32. Shao, Xiaofeng, 2010. "The Dependent Wild Bootstrap," Journal of the American Statistical Association, American Statistical Association, vol. 105(489), pages 218-235.
  33. Xiaofeng Shao, 2010. "A self‐normalized approach to confidence interval construction in time series," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 72(3), pages 343-366, June.
  34. Shao, Xiaofeng & Zhang, Xianyang, 2010. "Testing for Change Points in Time Series," Journal of the American Statistical Association, American Statistical Association, vol. 105(491), pages 1228-1240.
  35. Xiaofeng Shao, 2010. "Corrigendum: A self‐normalized approach to confidence interval construction in time series," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 72(5), pages 695-696, November.
  36. Shao, Xiaofeng, 2009. "A Generalized Portmanteau Test For Independence Between Two Stationary Time Series," Econometric Theory, Cambridge University Press, vol. 25(1), pages 195-210, February.
  37. Xiaofeng Shao, 2009. "Confidence intervals for spectral mean and ratio statistics," Biometrika, Biometrika Trust, vol. 96(1), pages 107-117.
  38. Wu, Wei Biao & Shao, Xiaofeng, 2007. "A Limit Theorem For Quadratic Forms And Its Applications," Econometric Theory, Cambridge University Press, vol. 23(5), pages 930-951, October.
  39. Shao, Xiaofeng & Wu, Wei Biao, 2007. "Local asymptotic powers of nonparametric and semiparametric tests for fractional integration," Stochastic Processes and their Applications, Elsevier, vol. 117(2), pages 251-261, February.
  40. Shao, Xiaofeng & Wu, Wei Biao, 2007. "Local Whittle Estimation Of Fractional Integration For Nonlinear Processes," Econometric Theory, Cambridge University Press, vol. 23(5), pages 899-929, October.
  41. X Zhang & C E Lee & X Shao, 0. "Envelopes in multivariate regression models with nonlinearity and heteroscedasticity," Biometrika, Biometrika Trust, vol. 107(4), pages 965-981.

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NEP Fields

NEP is an announcement service for new working papers, with a weekly report in each of many fields. This author has had 3 papers announced in NEP. These are the fields, ordered by number of announcements, along with their dates. If the author is listed in the directory of specialists for this field, a link is also provided.
  1. NEP-ETS: Econometric Time Series (3) 2018-03-19 2020-09-07 2022-10-10
  2. NEP-ECM: Econometrics (2) 2018-03-19 2022-10-10

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