Curriculum vitae

Currently I am an Associate Professor in the Institute of Statistics and Big Data at Renmin University of China. Before that, I was an Assistant Professor in Academy of Mathematics and Systems Science at Chinese Academy of Sciences since 2008 and also Research Fellow in Department of Statistics at London school of Economics and Political Science from 2014 to 2016.

I completed my Ph.D. in Mathematical Statistics from Academy of Mathematics and Systems Science at Chinese Academy of Sciences in 2008, advised by Professor Min Chen. From 2009 to 2010 I was a Visiting Postdoctoral Research Associate in the Department of Operations Research and Financial Engineering (ORFE) at Princeton University, hosted by Professor Jianqing Fan.

See my personal website: sites.google.com/site/guoshaojun20170709/

Technical Reports:

1. Guo, S., and Qiao, X. (2020). On Consistency and Sparsity for High-Dimensional Functional Time Series with Application to Autoregressions. Under Review.

2. Guo, S., Han, Y., and Wang, Q. (2020). Better Nonparametric Confidence Intervals via Robust Bias Correction for Quantile Regression. Revised and Resubmitted to Stat Journal.

3. Peng, S. Guo, S., and Long,Y. (2020). High Dimensional Portfolio Allocation via Mixed Frequency Dynamic Factor Models. Revised by Econometric Reviews.

Publications:

1. Chen, C., Guo, S., and Qiao, X. (2020). Functional Linear Regression: Dependence and Error Contamination. Forthcoming in Journal of Business and Economic Statistics.

2. Ma, Y., Guo, S., and Wang, H. (2020). Sparse Spatio-Temporal Autoregressions by Profiling and Bagging. Forthcoming in Journal of Econometrics.

3. Qiao, X., Qian, C., James, G. and Guo, S. (2020). Doubly Functional Graphical Models in High Dimensions. Biometrika. Vol 107, Issue 2, 415-431.

4. Guo, S., Li, D. and Li, M. (2019). Strict stationarity testing and GLAD estimation of double autoregressive models. Journal of Econometrics. Vol 211, Issue 2, 319-337.

5. 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.

6. Qiao, X., Guo, S. and James, G. (2019). Functional graphical models. Journal of the American Statistical Association. Vol 114, 525, 211-222.

7. Li, D., Guo, S. and Zhu, K. (2019). Double AR model without intercept: an alternative to modeling nonstationarity and heteroscedasticity. Econometric Reviews, Vol 38, No.3, 319-331.

8. 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, 517, Vol 112, 235-253.

9. Guo, S., Wang, Y. and Yao, Q. (2016). High dimensional and banded vector autoregressions. Biometrika, 103, 889-903.

10. Guo, S. and Zeng, D. (2014). An overview of semiparametric models in survival analysis. (Invited article). Journal of Statistical Planning and Inference. 151-152, 1-16.

11. 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.

12. Fan, J., Guo, S. and Hao, N. (2012). Variance estimation using refitted cross-validation in ultra-high dimensional regression. Journal of the Royal Statistical Society, Series B, 74, 37-65.

13. 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.

14. Chen, K., Guo, S., Lin, Y. and Ying, Z. (2010). Least absolute relative error estimation. Journal of the American Statistical Association, 105, 1104-1112.

15. 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.

16. 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.

17. 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.