PUBLICATIONS

[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.C, 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, 10,220–10,236.
[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.