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常晋源

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:

    14. Chang, J., Qiu, Y., Yao, Q. & Zou, T. (2018). Confidence regions for entries of a large precision matrix,Journal of Econometrics, in press.

    13. Chang, J., Tang, C. Y. & Wu, T. T. (2018). A new scope of penalized empirical likelihood with high-dimensional estimating equations,The Annals of Statistics, in press.

    12. Chang, J., Guo, B. & Yao, Q. (2018). Principal component analysis for second-order stationary vector time series,The Annals of Statistics, in press.

    11. Chang, J., Delaigle, A., Hall, P. & Tang, C. Y. (2018). A frequency domain analysis of the error distribution from noisy high-frequency data,Biometrika, 105, 353-369.

    10. Chang, J., Zheng, C., Zhou, W.-X. & Zhou, W. (2017). Simulation-based hypothesis testing of high dimensional means under covariance heterogeneity,Biometrics, 73, 1300-1310.

    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, 73, 31–41.

    8. Chang, J., Yao, Q. & Zhou, W. (2017). Testing for high-dimensional white noise using maximum cross-correlations,Biometrika, 104, 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, 44, 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, 44, 515–539.

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

    4. Chang, J. & Hall, P. (2015). Double-bootstrap methods that use a single double-bootstrap simulation,Biometrika, 102, 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, 185, 283–304.

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

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