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常晋源
  • 常晋源
  • 系别:西南财经大学统计研究中心
  • 职称:教授
  • 办公电话:0
  • Email:changjinyuan@swufe.edu.cn
  • 教师简介
  • 研究成果
  • 学术活动
  • 教授课程
  • 研究领域:高维数据分析、经验似然、金融计量

    教育经历:

    2009—2013 经济学博士、北京大学光华管理学院

    2005—2009 理学学士、北京师范大学数学科学学院

    学术服务:

    2017.10—至今   Journal of the Royal Statistical Society Series B 副主编(Associate Editor)

    2017.08—至今   Statistica Sinica 副主编(Associate Editor)

     

  • 已发表论文:

     

    13. Chang, J., Delaigle, A., Hall, P. & Tang, C. Y. (2017). A frequency domain analysis of the error distribution from noisy high-frequency data, Biometrika, in press.

    12. Chang, J., Tang, C. Y. & Wu, T. T. (2017). A new scope of penalized empirical likelihood with high-dimensional estimating equations, The Annals of Statistics, in press.

    11. Chang, J., Guo, B. & Yao, Q. (2017). Principal component analysis for second-order stationary vector time series, The Annals of Statistics, in press.

    10. Chang, J., Zheng, C., Zhou, W.-X. & Zhou, W. (2017). Simulation-based hypothesis testing of high dimensional means under covariance heterogeneity, Biometrics, in press.

      9. Chang, J., Zhou, W., Zhou, W.-X. & Wang, L. (2017). Comparing large covariance matrices under weak conditions on the dependence structure and its application to gene clustering, Biometrics, Vol. 73, pp. 31–41.

      8. Chang, J., Yao, Q.  & Zhou, W. (2017). Testing for high-dimensional white noise using maximum cross-correlations, Biometrika, Vol. 104, pp. 111–127.

      7. Chang, J., Shao, Q.-M.  & Zhou, W.-X. (2016). Cramer-type moderate deviations for Studentized two-sample U-statistics with applications, The Annals of Statistics, Vol. 44, pp. 1931–1956.

      6. Chang, J., Tang, C. Y. & Wu, Y. (2016). Local independence feature screening for nonparametric and semiparametric models by marginal empirical likelihood, The Annals of Statistics,Vol. 44, pp. 515–539.  

      5. Chang, J., Guo, B. & Yao, Q. (2015). High dimensional stochastic regression with latent factors, endogeneity and nonlinearity, Journal of Econometrics, Vol. 189, pp. 297–312.

      4. Chang, J. & Hall, P. (2015). Double-bootstrap methods that use a single double-bootstrap simulation, Biometrika, Vol. 102, pp. 203–214.

      3. Chang, J., Chen, S. X.  & Chen, X. (2015). High dimensional generalized empirical likelihood for moment restrictions with dependent data, Journal of Econometrics, Vol. 185, pp. 283–304.

      2. Chang, J., Tang, C. Y.  & Wu, Y. (2013). Marginal empirical likelihood and sure independence feature screening, The Annals of Statistics, Vol. 41, pp. 2123–2148.

      1. Chang, J.  & Chen, S. X. (2011). On the approximate maximum likelihood estimation for diffusion processes, The Annals of Statistics, Vol. 39, pp. 2820–2851. 

     

      邀请讨论和综述文章:  

      1. Chang, J., Guo, J. & Tang, C. Y. (2017). Peter Hall’s contribution to empirical likelihood, Statistica Sinica, in press.

     

     

     


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