郭绍俊 职称：副教授、博士生导师（统计与大数据研究院）
研究方向：统计学习；非参数及半参数统计建模；生存分析及函数型数据分析
联系方式：sjguo@ruc.edu.cn


个人简历现为中国人民大学统计与大数据研究院副教授。2003年本科毕业于山东师范大学，2008年获得中国科学院数学与系统科学研究院理学博士学位。博士毕业后留中国科学院数学与系统科学研究院工作，助理研究员，任期至2016年。2009年-2010年赴美国普林斯顿大学运筹与金融工程系博士后研究，做高维数据分析方面的研究工作，并于2014-2016年在英国伦敦经济学院统计系做博士后研究，做大维时间序列建模方面的研究。
目前主要研究方向有：统计学习；非参数及半参数统计建模；生存分析及函数型数据分析等。


详见个人网页：https://sites.google.com/site/guoshaojun**/


Technical Reports:
* Qiao, X., Qian, C., James, G. and Guo, S. (2019). Doubly Functional Graphical Models in High Dimensions. Under second round revision in Biometrika.
* Guo, S. and Qiao, X. (2019). A General Theory for Large Scale Curve Time Series via Functional Stability Measure. Submitted.
* Qiao, X., Chen, C, and Guo, S. (2019). Functional Linear Regression: Dependence and Error Contamination. Submitted.


Selected Publications:


* Guo, S., Li, D. and Li, M. (2019). Strict stationarity testing and estimation for double autoregressive models.Forthcoming in Journal of Econometrics . [pdf]
* Qiao, X., Guo, S. and James, G. (2019). Functional Graphical Models. Jou r nal of the American Statistical Association, Vol 114, 525, 211-222 . [pdf]
* Li, N., Guo, S., and Wang. Y. (2019). Weighted Preliminary-Summation-Based Principal Component Analysis for Non-Gaussian Processes. Control Engineering Practice, Vol 87, 122-132.
* Li, D., Guo, S. and Zhu, K. (2019). A double AR model without intercept: an alternative to modeling nonstationarity and heteroscedasticity. Econometric Reviews. Vol 38, No.3, 319-331. [pdf] [arxiv]
* Guo, S., Box, J. and Zhang W. (2017). A dynamic structure for high dimensional covariance matrices and its application in portfolio allocation. Journal of the American Statistical Association ，Vol 112，517，235-253. [pdf] [online]
* Guo, S., Wang, Y. and Yao, Q. (2016). High dimensional and banded vector autoregressions. Biometrika , 103(4): 889-903. [pdf] [Supplemental] [arxiv]
*Guo, S. and Zeng, D. (2014). An overview of semiparametric models in survival analysis. Journal of Statistical Planning and Inference , V151-152, 1-16. [pdf] [online]
* Guo, S., Ling, S. and Zhu, K. (2014). Factor double autoregressive models with application to simultaneous causality testing. Journal of Statistical Planning and Inference, 148, 82-94. [pdf][online]
* Fan, J., Guo, S. and Hao, N. (2012). Variance estimation using refitted cross-validation in ultrahigh dimensional regression. Journal of the Royal Statistical Society, Series B , 74,37-65. [pdf] [online]
* Sun, L., Zhou, X. and Guo, S. (2011). Marginal regression models with time-varying coefficients for recurrent event data. Statistics in Medicine , 30, 2265-2277. [pdf] [online]
* Chen, K. , Guo, S., Lin, Y. and Ying, Z. (2010). Least absolute relative error estimation. Journal of the American Statistical Association , 105, 1104-1112. [pdf]] [online]
* Chen, K., Guo, S., Sun, L. and Wang, J. L. (2010). Global partial likelihood for nonparametric proportional hazards model. Journal of the American Statistical Association , 105, 750-760. [pdf][online]
* Sun, L., Guo, S. and Chen, M. (2009). Marginal regression model with time-varying coefficients for panel data. Communications in Statistics: Theory and Methods , 38, 1241-1261. [pdf] [online]
* Wong, H., Guo, S., Chen, M., and Ip, W. C. (2009). On locally weighted estimation and hypothesis testing on varying coefficient models with missing covariates. Journal of Statistical Planning and Inference , 139, 2933-2951. [pdf] [online]