Citation Profile：H-index 32, Web of Science , I-10 Index 59,   Total SCI Citations (without self citation) 3486

Publications
[113] Chen，SX, Guo, B. and Qiu, YM (2022) Testing and Signal Identification for Two-sample High-dimensional Covariances via Multi-level Thresholding, Journal of Econometrics, to appear.
[112] Luo, S., Zhu, Y., & Chen, S. X. (2022). Episode based air quality assessment. Atmospheric Environment, 285, 119242.
[111] Li, S-M, Liu, R., Wang, S. and S.X. Chen (2021). Radiative Effects of Particular Matters on Ozone Pollution in Six North China Cities, Journal of Geophysical Research, Vol.126, No. 24, e2021JD035963.
[110] 陈松蹊，毛晓军，王聪 （2021）大数据情境下的数据完备化：挑战与对策。 管理世界，2022年第1期，196-206。
[109] Huang, YX., B. Guo, H. Sun, H. Liu and S. X. Chen(2021) Relative Importance of Meteorological Variables on Air Quality and Role of Boundary Layer Height, Atmospheric Environment,267,118737.
[108] 王振中, 陈松蹊, 涂云东 (2021)，中国居民消费价格指数的动态结构研究及中美量化比较, 数理统计与管理，12（01）：18。
[107] 顾嘉 , 陈松蹊, 董倩, 邱宇谋 (2021）基于vSEIdRm模型的人口迁移以及武汉封城对新冠肺炎疫情发展的影响分析，统计研究，Vol.38, No.9。
[106] Yan, H., Zhu, YR., Gu, J., Huang, YX., Sun, HX., Zhang, XY., Wang, YT., Qiu, YM. and Chen, S.X. (2021). Better strategies for containing COVID-19 pandemic: a study of 25 countries via a vSIADR model, Proceedings of the Royal Society A, 476: 20200440.
[105] Zhu, Y.R.，Liang, Y.S. and Chen, S.X. (2021) Assessing Local Emission for Air Pollution via Data Experiments, Atmospheric Environment, 252, 118323.
[104] [104] Chen, S.X. and L-H Peng (2021) Distributive statistical inference for massive data, The Annals of Statistics, 49, 2851–2869.
[103] Chang, J-Y., Chen, S.X., Tang, C-Y. and Wu, T-T (2021) High-dimensional empirical likelihood inference, Biometrika, 108, 127-147.
[102] Zhang, HM and Chen, S. X. (2021), Concentration Inequalities for Statistical Inference (Review Paper), Communications in Mathematical Research, 37, 1-85. doi: 10.4208/cmr.2020-0041
[101] Chen, S.X. and Zheng, XY (2021) Discussion of ``The timing and effectiveness of implementing mild interventions of COVID-19 in large industrial regions via a synthetic control method", Statistics and Its Interface, 14, 23-24
[100] Zheng, X-Y., Guo, B., He, J. and Chen, S.X. (2021) Effects of COVID-19 Control Measures on Air Quality in North China (Invited Paper), Envirionmentrics, Volume 32, Issue 2，e2673.
[99] 吴煌坚，林伟，孔磊，唐晓，王威，王自发，陈松蹊 (2021) 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》, 第26卷第2期。
[98]Zhang, S., Chen, S.X. and Lu, L. (2021), Inference for Variance Risk Premium, China Finance Review International, 11, 26-52.
[97] Mao, X-J., Wong, R. K-W and Chen, S. X. (2021) Matrix Completion under Low-Rank Missing Mechanism, Statistica Sinica, 31, 2005-2030.
[96]Wu, 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.
[95]Wan, Y., Xu, M., Huang, H. and Chen, S.X. (2020) A spatio-temporal model for the analysis and prediction of fine particulate matter concentration in Beijing, Enviromentrics, 32 (1), e2648.
[94]Haoxuan Sun, Yumou Qiu, Han Yan, Yaxuan Huang, Yuru Zhu, Jia Gu and Song Xi Chen(2020) Tracking Reproductivity of COVID-19 Epidemic in China with Varying Coefficient SIR Model (with discussion)，Journal of Data Science 18 (3), 455–472.
[93]Ziping 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.
[92] Shuyi Zhang, Song Xi Chen, Bin Guo, Hengfang Wang, Wei Lin (2020) Regional Air-Quality Assessment That Adjusts for Meteorological Confounding, Science China Mathematics, 50, 527-558.
[91]Gu, J., Yan, H., Huang, J., Zhu, Y., Sun, H., Qiu, Y. and S. X. Chen（2020）, Comparing Containment Measures among Nations by Epidemiological Effects of COVID-19. National Science Review, 7: 1847–1851. doi: 10.1093/nsr/nwaa243.
[90] Zheng, XY and Chen, SX (2019)  Partitioning Structure Learning for Segmented Linear Regression Trees,  Advances in Neural Information Processing Systems (NeurIPS), 2019.
[89] Mao, 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
[88] Chen, S.X., Li, J. and P.-S. Zhong, (2019) Two-Sample and ANOVA Tests for High Dimensional Means, The Annals of Statistics, 47, 1443-1474.
[87] Li, 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.
[86] J. He and S. X. Chen (2018) High-Dimensional Two-Sample Covariance Matrix Testing via Super-diagonals, Statistica Sinica, 28, 2671-2696.
[85] Chen, L., Guo, B., Huang, J, He, J., Wang, H., Shuyi Zhang, and S.X. Chen (2018). Assessing air-quality in Beijing-Tianjing-Hebei region: the method and mixed tales of PM2.5 and O3. Atmospheric Environment, 193, 290-301.
[84] Qiu, Y., Chen, S.X. and Nettleton, D.（2018）Detecting Rare and Faint Signals via Thresholding Maximum Likelihood Estimators, Annals of Statistics, 46, 895-923.
[83] Zhang, SY, Guo, B. Dong, A., He, J., Xu, Z and Chen, SX (2017) Cautionary Tales on Air Quality Improvement in Beijing, Proceedings of the Royal Society A,  473: 20170457.
[82] Zuo, T. and S. X. Chen (2017).  Enhancing Estimation for Interest Rate Diffusion Models with Bond Prices. Journal of Business and Economics Statistics, 35:3, 486-498.
[81] Guo, B. and S.X.Chen (2016).   Tests for High Dimensional Generalized Linear Models. Journal of the Royal Statistical Society, Series B. to 1079-1102.
[80] Wang, Y., Tu, Y-D and S. X. Chen (2016) Improving inflation prediction with the quantity theory. Economics Letters, 149, 112-115.
[79] Chen, S.X. (2016) 　Peter Hall's Contribution to the Bootstrap, The Annals of Statistics, 44, No. 5, 1821–1836.
[78] 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(17), 10220–10236.
[77] 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.
[76] He, J. and S. X. Chen (2016) Testing Super-Diagonal Structure in High Dimensional Covariance Matrices, Journal of Econometrics, 194,  283-297
[75] 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.
[74] Liang, X., T, Zuo, 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.
[73] 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.
[72] 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.
[71] 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.
[70] Chen, S.X. and Z. Xu (2013). On smoothing estimation for seasonal time series with long cycles, Statistics and Its Interface, 6, 435-447.
[69] Chen, S. X., Peng, L. and C. L. Yu (2013). Parameter Estimation and Model Testing for Markov Processes via Conditional Characteristic Functions, Bernoulli, 19, 228-251.
[68] Chen, S. X. and Van Keilegom, I. (2013). Estimation in semiparametric models with missing data. Annals of the Institute of Statistical Mathematics, 65, 785-805.
[67] Chen, S. X., Tang, C.Y. and J. Qin (2013). Mann-Whitney Test with Adjustments to Pre-treatment Variables for Missing Values and Observational Study, Journal of the Royal Statistical Society, Series B., 75, 81-102.
[66] 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.
[65] Li, J. and S. X. Chen (2012). Two Sample Tests for High Dimensional Covariance Matrices, The Annals of Statistics, 40, 908-940.
[64] 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.
[63] Chen, S. X. and C. Y. Tang (2011). Nonparametric Regression with Discrete Covariates and Missing Value. Statistics and Its Interface, 4, 463-474.
[62] J. Chang and S.X. Chen (2011). On the approximate maximum likelihood estimation for diffusion processes. The Annals of Statistics, 39, 2820-2851.
[61] Chen, S. X. and C. Y. Tang (2011). Properties of Census Dual System Population Size Estimators. International Statistical Review, 79, 336-361.
[60] 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.
[59] 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.
[58] Alzghool, R., Y-X Lin and S. X. Chen (2010). Asymptotic Quasi-likelihood Based on Kernel Smoothing for Multivariate Heteroskedastic Models with Correlation, American Journal Of Mathematical And Management Sciences,  30, 147-177.
[57] Chen, S. X. and P-S Zhong (2010). ANOVA for longitudinal data with missing values. The Annals of Statistics, 38, 3630-3659.
[56] 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.
[55] Chen, S. X., Delaigle, A. and Hall, P. (2010). Nonparametric estimation for levy-type processes, Journal of Econometrics, 157, 257-271.
[54] 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.
[53] Chen, S. X., C. Y. Tang and V. T. Mule Jr. (2010). Local Post-Stratification in Dual System Accuracy and Coverage Evaluation for US Census,  Journal of the American Statistical Association, Application & Case Studies, 105, 105-119.
[52] Chan, N-H, Chen, S.X., Peng, L. and C. L. Yu (2009). Empirical Likelihood Methods Based on Characteristic Functions with Applications to L\'evy Processes. Journal of the American Statistical Association, 104, 1621-1630.
[51] Chen, S. X. and I. Van Keilegom (2009). A review on empirical likelihood for regressions (with discussions), Test, 3, 415-447 .
[50] Chen, S. X. and Van Keilegom, I. (2009). Empirical likelihood test for a class of regression models. Bernoulli, 15, 955-976.
[49] C. Y. Tang and S. X. Chen (2009). Parameter estimation and bias correction for diffusion processes. Journal of Econometrics, 149, 65—81.
[48] Chen, S. X., L. Peng and Y-L, Qin (2009). Effects of Data Dimension on Empirical Likelihood, Biometrika, 96, 711–722.
[47] Wang, D. and S.X. Chen (2009). Empirical Likelihood for  Estimating Equation with Missing Values. The Annals of Statistics, 37, 490–517.
[46] Wang, D. and Chen, S. X. (2009). Combining quantitative trait loci analyses and microarray data, an empirical likelihood approach. Computational Statistics and Data Analysis, 53, 1661–1673.
[45] Chen, S.X. and Chiumin Wong (2009). Smoothed Block Empirical Likelihood for Quantiles of Weakly Dependent Processes, Statist Sinica, 19, 71-82.
[44] Chen, S. X., Leung, D. Y. H. and J. Qin (2008). Improved Semiparametric Estimation Using Surrogate Data. Journal of the Royal Statistical Society, Series B, 70, 803-823.
[43] Chen, S.X., J. Gao and C. Y. Tang (2008). A Test for Model Specification of Diffusion Processes. The Annals of Statistics, 36, 167-198.
[42] Chen, S.X: (2008). Nonparametric Estimation of Expected Shortfall. Journal of Financial Econometrics, 6, 87-107.
[41] Chen, S. X. and T. Huang (2007). Nonparametric Estimation of Copula Functions for Dependent Modeling. Canadian Journal of Statistics, 35, 265-282.
[40] 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.
[39] Chen, S.X. and J. Gao (2007). An Adaptive Empirical Likelihood Test For Time Series Models, paper, full report, Journal of Econometrics, 141, 950-972.
[38] Chen, S.X. and H.-J., Cui (2006). On Bartlett Correction of Empirical Likelihood in the Presence of Nuisance Parameters, Biometrika, 93, 215-220.
[37] Chen, S.X. and Qin, J. (2006). An Empirical likelihood Method in Mixture Models with Incomplete Classifications, Statistica Sinica,16, 1101-1115.
[36] Chen, S. X. and Tang, C. Y. (2005). Nonparametric Inference of Value at Risk for dependent Financial Returns. Journal of Financial Econometrics, 3, 227-255.
[35] Chen, S. X. and Qin, Y-S. (2003). Coverage accuracy of confidence intervals in nonparametric regression. Acta Math. Appl. Sin. Engl. Ser.19,387--396.
[34] Chen, S. X., D. H. Y. Leung and Qin, J. (2003). Information Recovery in a Study with Surrogate Endpoints.  Journal of the American Statistical Association, 98,1052--1062.
[33] Chen, S. X. and Qin, J. (2003). Empirical likelihood based confidence intervals for data with possible zero observations. Statistics and Probability Letters, 65, 29-37.
[32] Chen, S. X., Haredle, W. and Li, M. (2003). An empirical likelihood goodness-of-fit test for time series. Journal of The Royal Statistical Society, Series B, 65, 663-678.
[31] Chen, S. X. and Hall, P. (2003). Effects of bagging and bias correction on estimators defined by estimating equations, Statistica Sinica,13, 97-109.
[30] Chen, S. X and Cui, H-J. (2003). An extended empirical likelihood for generalized linear models. Statistica Sinica, 13, 69-81.
[29] Chen, S. X. and Hall, P. (2003). EFFECTS OF BAGGING AND BIAS CORRECTION ON ESTIMATORS DEFINED BY ESTIMATING EQUATIONS, Statistica Sinica, 13, 97-109.
[28] Chen, S. X., Hardle, W. and Kleinow, T. (2002). An empirical likelihood goodness-of-fit test for diffusions. Applied quantitative finance, 259--281, Springer, Berlin.
[27] Chen, S. X, Yip, P. and Zhou, Y. (2002). Sequential line transect surveys. Biometrics, 58, 263-269.
[26] Chen, S. X. (2002). Local linear smoothers using asymmetric kernels. Ann. Inst. Statist. Math., 54, 312-323.
[25] Chen, S. X. and Lloyd, C. J.(2002). Estimation of population size based on biased samples using nonparametric binary regression.  Statist. Sinica, 12, 505-518.
[24] Chen, S. X. and Qin, Yong Song (2002). Confidence interval based on a local linear smoother. Scand. J. Statist., 29, 89-99.
[23] Chen, S. X. and Cowling, A. (2001). Measurement Errors in Line Transect Surveys where Detection varies with Distance and Size. Biometrics, 57, 732-742.
[22] Chen, S. X. and Qin, Yong Song (2000). Empirical Likelihood confidence interval for a local linear smoother. Biometrika, 87, 946-953.
[21] Chen, S. X. and Lloyd, C. J. (2000). A non-parametric approach to the analysis of two stage mark-recapture experiments.Biometrika, 87, 633-649.
[20] Chen, S. X. (2000). Gamma kernel estimators for density functions. Ann. Inst. Statist. Math. 52, 471-480.
[19] Chen, S. X. (2000). Animal abundance estimation for independent observer line transect surveys. Special Issue of Environmental and Ecological Statistics: Statistical Ecology and Forest Biometry 7, No. 3, 285-299.
[18] Chen, S. X. (2000). Beta kernel smoothers for regression curves. Statistica Sinica.10, 73-91.
[17] Chen, S. X. (1999). Beta kernel estimators for density functions. Computational Statistics and Data Analysis, 31, 131-145.
[16] Chen, S. X. and Woolcock, J. (1999). A condition for designing bus-route type access site surveys to estimate recreational fishing effort. Biometrics. 55, No. 3, 799-804.
[15] Chen, S. X. (1999). Estimation in independent observer line transect surveys for clustered populations. Biometrics, 55 , No. 3, 754-759.
[14] Brown, B. M. and Chen, S. X. (1999). Beta-Bernstein smoothing for regression curves with compact support. Scand. J. Statist. . 26, 47-59.
[13] Brown, B. M. and Chen, S. X. (1998). Combined Empirical Likelihood. Ann. Inst. Statist. Math, 50, 697-714.
[12] Chen, S.X. (1998). Measurement errors in line transect surveys. Biometrics, 54, 899-908.
[11] Chen, S.X. (1997). Empirical likelihood for nonparametric density estimation. Aust. J. Statist. , 39,47-56
[10] Chen, S.X. and Polacheck, T. (1996). Kernel estimates of mean school size for IWC minke whale data. Report of International Whaling Commission, 46, 341-348.
[9] Chen, S.X. (1996). Empirical likelihood confidence intervals for nonparametric density estimation. Biometrika, 83, 329-341.
[8] Chen, S.X. (1996). Studying school size effects in line transect sampling using the kernel method. Biometrics , 52, 1283-94.
[7] Chen, S.X. (1996). A kernel estimate for density of a biological population using line transect sampling. Royal Statistical Society Ser. C: Applied Statistics, 45, 135-150.
[6] Chen, S.X. (1994). Comparing empirical likelihood and bootstrap hypothesis tests. J. Mult. Anal, 51, 277-293.
[5] Chen, S.X. (1994). Empirical likelihood confidence intervals for linear regression coefficients. J. Mult. Anal. 49, 24-40.
[4] Chen, S.X. and Hall, P. (1994). On the calculation of standard error for quotation in confidence statements. Statistics and Probability Letters,19,147-151.
[3] Chen, S.X. and Hall, P. (1993). Smoothed empirical likelihood confidence intervals for quantiles. Ann. Of Statistics, 21,1166-1181.
[2] Chen, S.X. (1993). On the coverage accuracy of empirical likelihood confidence regions for linear regression model. Annals of Institute of Statistical Mathematics, 45, 621-637.
[1] Chen, S.X., Smith, P.J., Shafi, M. and Vere-Jones, D. (1990). Some improvements to conventional importance sampling techniques for coded system using Viterbi decoding. Electronics Letters, 26, 802-806.

Environmental statistics； empirical likelihood: second order properties and various applications
analysis on missing data; multiple system surveys for us census
inference for stochastic processes
inference for high dimensional data
 

1. Special Topics in Statistics (PHD Program)

2. Advanced Econometrics (PHD Program)

3. A Computer-Intensive Statistical Methods, Spring 2007

4. Multivariate Analysis, Fall 2006

5. Advanced Theory of Statistical Inference (Ph.D. Core), Spring 2006

6. Nonparametric Statistical Models, Fall 2005

7. Advanced Theory of Statistical Inference (Ph.D. Core), Spring 2005