Air Quality Assessment  

Develop statistical methods to measure the effectiveness of the air pollution mitigation strategies based on objective air quality measures that remove the meteorological confounding.

1Zheng, X-Y. and Chen, S.X. (2020) Dynamic Synthetic Control Method for Evaluating Effects of Air Pollution Alerts.[pdf] 
2Zheng, X-Y., Guo, B., He, J. and Chen, S.X. (2020) Effects of COVID-19 Control Measures on Air Quality in North China, Envirionmentrics (Discussion Paper) to appear[pdf] 
3吴煌坚,林伟,孔磊,唐晓,王威,王自发,陈松蹊 (2020) 一种基于集合最优插值的排放源快速反演方法, 《气候与环境研究》, 接受。[pdf] 
4Shaomin Li, Rui Liu and Song Xi Chen(2020) Radiative Effects of Particular Matters on Ozone Pollution in Six Northern China Cities, revised for Journal of Geophysical Research[pdf] 
5Wu, H., Zheng, X., Zhu, J., Lin, W., Zheng, H., Chen, X., Wang, W., Wang, Z., and S. X. Chen (2020). Improving PM2.5 forecasts in China suing an initial error transport model, Environmental Science and Technology, 54(17), 10493-10501.[pdf] 
6Yating Wan, Minya Xu, Hui Huang and Song Xi Chen(2020) A spatio-temporal model for the analysis and prediction of fine particulate matter concentration in Beijing, Enviromentrics, to appear.[pdf] 
7Shuyi Zhang, Song Xi Chen, Bin Guo, Hengfang Wang, Wei Lin (2020) Regional Air-Quality Assessment That Adjusts for Meteorological Confounding​, Science China Mathematics (in Chinese) 50, 527-558.[pdf] 
8Ziping Xu, Song Xi Chen, Xiaoqing Wu (2020) Meteorological Change and Impacts on Air Pollution Results from North China, Journal of Geophysics Research-Atmosphere, 125 (16), e2020JD032423.[pdf] 
9Li, HB, Wu, JW., Wang, AX, Li, X, Chen, SX, Wang, TQ, Amsalu, E., Gao, Q., Luo, YX, Yang, XH., Wang, W, Guo, J., Guo, YM, Guo, XH. (2018). Effects of ambient carbon monoxide on daily hospitalizations for cardiovascular disease: a time-stratified case-crossover study of 460,938 cases in Beijing, China from 2013 to 2017, ENVIRONMENTAL HEALTH, 17:82.[pdf] 
10Lei Chen, Bin Guo, Jiasheng Huang, Hengfang Wang, Shuyi Zhang and Song Xi Chen (2018). Assessing Air-Quality in Beijing-Tianjin-Hebei Region: the Method and Mixed Tales of PM2.5 and O3. Atmospheric Environment 193 (2018) 290–301.[pdf] 
11Zhang S, Guo B, Dong A, He J, Xu Z, Chen SX. 2017 Cautionary tales on air-quality improvement in Beijing. Proc. R. Soc. A 20170457.[pdf] 
12 Liang, X., Li, S., Zhang, SY, Huang, H. and S.X. Chen (2016). PM2.5 Data Reliability, Consistency and  Air Quality Assessment in Five Chinese Cities,  Journal of Geophysical Research:Atmosphere,  121, 10,220_10,236.[pdf] 
13 Liang, X., T. Zou, B. Guo, S. Li, H. Zhang, S. Zhang, H. Huang and S. X. Chen. (2015). Assessing Beijing's PM2.5 Pollution: Severity, Weather Impact, APEC and Winter Heating, Proceedings of the Royal Society A, 471, 20150257.[pdf] 

High Dimensional Statistical Inference  

Development methods applicable to a new norm of data: the dimension of the data is much larger than the number of sample points as commonly encountered in genetic and bio-medical studies, brain imaging and social and economic analyses.

1 Mao, X-J., Wong, R. K-W and Chen, S. X. (2020) Matrix Completion under Low-Rank Missing Mechanism, Statistica Sinica, to appear.[pdf] 
2Mao, X., Chen, SX and Wong, R.(2019) Matrix Completion with Covariate Information, Journal of the American Statistical Association, 2019, VOL. 114, NO. 525, 198–210, Theory and Methods[pdf] 
3S.X. Chen, J. Li and P.-S. Zhong (2019), Two-Sample and ANOVA Tests for High Dimensional Means, The Annals of Statistics, Vol. 47, No. 3, 1443-1474.[pdf] Code 
4Qiu, Y., Chen, S.X. and Nettleton, D.(2018)Detecting Rare and Faint Signals via Thresholding Maximum Likelihood Estimators, Annals of Statistics, 46, 895-923. [pdf] 
5Jing He and Song Xi Chen (2018). High-Dimensional Two-Sample Covariance Matrix Testing via Super-Diagonals. Statistica Sinica 28 (2018), 2671-2696[pdf] 
6 Guo, B. and S.X.Chen (2016). Tests for High Dimensional Generalized Linear Models. Journal of the Royal Statistical Society, Series B. 78, 1079–1102.[pdf] Code 
7 Peng, LH, S.X. Chen and W, Zhou (2016) More Powerful Tests for Sparse High-Dimensional Covariances Matrices, Journal of Multivariate Analysis,  149, 124-143.[pdf] Code 
8 He, J. and S. X. Chen (2016) Testing Super-Diagonal Structure in High Dimensional Covariance Matrices, Journal of Econometrics, 194,  283-297[pdf] Code 
9 Chang, J-Y, Chen, S.X. and X. Chen (2015). High Dimensional Generalized Empirical Likelihood for Moment Restrictions with Dependent Data. Journal of Econometrics, 185, 283-304.[pdf] 
10 Qiu, Y-M and Chen, S.X. (2015)  Band Width Selection for High Dimensional Covariance Matrix Estimation. Journal of the American Statistical Association, 110, 1160-1174.[pdf] Code 
11 Zhong, P-S, Chen, S. X. and Xu M. (2013). Tests alternative to higher criticism for high dimensional means under sparsity and column-wise dependence, Annals of Statistics, 41, 2820-2851.[pdf] Code 
12 Qiu, Y-M and Chen, S. X. (2012). Test for Bandedness of High Dimensional Covariance Matrices with Bandwidth Estimation, TheAnnals of Statistics, 40, 1285-1314.[pdf] Code 
13 Li, J. and S. X. Chen (2012). Two Sample Tests for High Dimensional Covariance Matrices, The Annals of Statistics, 40, 908-940.[pdf] Code 
14 P-S Zhong and S. X. Chen (2011). Tests for High Dimensional Regression Coefficients with Factorial Designs. Journal of the American Statistical Association, 106, 260-274.[pdf] Code 
15 Chen, S.X., Zhang, L-X. and P-S Zhong (2010). Testing high dimensional covariance matrices. Journal of the American Statistical Association, 105, 810-819.[pdf] Code 
16 Chen, S. X. and Y. L. Qin (2010). A two sample test for high dimensional data with application to gene-set testing, The Annals of Statistics, 38, 808-835.[pdf] Code 
17 Chen, S. X., L. Peng and Y-L, Qin (2009). Effects of Data Dimension on Empirical Likelihood, Biometrika, 96, 711_722.[pdf] 


Modeling and analyses of Chinese economic data and general econometric methods.

1Tao Zou & Song Xi Chen (2017) Enhancing Estimation for Interest Rate Diffusion Models With Bond Prices, Journal of Business & Economic Statistics, 35:3, 486-498[pdf] 
2 Wang, Y., Tu, Y-D and S. X. Chen (2016) Improving inflation prediction with the quantity theory. Economics Letters, 149, 112-115.[pdf] 
3 He, J. and S. X. Chen (2016) Testing Super-Diagonal Structure in High Dimensional Covariance Matrices, Journal of Econometrics, 194,  283-297[pdf] Code 
4 Chen, S.X., Lei, L.-H. and Tu, Y-D (2016). Functional Coefficient Moving Average Models with applications to forecasting Chinese CPI, Statistica Sinica, 26, 1649-1672. [pdf] 
5 Chang, J-Y, Chen, S.X. and X. Chen (2015). High Dimensional Generalized Empirical Likelihood for Moment Restrictions with Dependent Data. Journal of Econometrics, 185, 283-304.[pdf] 
6 Chen, S.X. and Z. Xu (2014). On Implied Volatility for Options - Some Reasons to Smile and More to Correct. Journal of Econometrics, 179, 1-15.[pdf] 
7 Chen, S.X. and Z. Xu (2013). On smoothing estimation for seasonal time series with long cycles, Statistics and Its Interface, 6, 435-447.[pdf] 
8 J. Chang and S.X. Chen (2011). On the approximate maximum likelihood estimation for diffusion processes. The Annals of Statistics, 39, 2820-2851.[pdf] 
9 Chen, S.X. and J. Gao (2011).  Simultaneous Specification Test for the Mean and Variance Structures for Nonlinear Time Series regression. Econometric Theory, 27, 2011, 792_843.[pdf] 
10 Chen, S. X., Delaigle, A. and Hall, P. (2010). Nonparametric estimation for a class of levy processes, Journal of Econometrics, 157, 257-271.[pdf] 
11 C. Y. Tang and S. X. Chen (2009). Parameter estimation and bias correction for diffusion processes. Journal of Econometrics, 149, 65-81.[pdf] 
12Chen, S.X: (2008). Nonparametric Estimation of Expected Shortfall. Journal of Financial Econometrics, 6, 87-107.[pdf] 
13  Chen, S.X. and H.-J., Cui (2007). On the second order properties of empirical likelihood with moment restrictions , Journal of Econometrics, 141, 492-516.[pdf] 
14Chen, S.X. and J. Gao (2007). An Adaptive Empirical Likelihood Test For Time Series Models, paper, full report, Journal of Econometrics, 141, 950-972.[pdf] 
15Chen, S. X. and Tang, C. Y. (2005). Nonparametric Inference of Value at Risk for dependent Financial Returns. Journal of Financial Econometrics, 3, 227-255.[pdf]