陈松蹊编辑

中国科学院院士、数学家

陈松蹊

陈松蹊，男，1961年11月出生于北京市，数学家，统计学家，中国科学院院士，北京大学教授、讲席教授。1983年，陈松蹊毕业于北京师范大学，获数学学士学位；1988年，毕业于北京师范大学，获数学硕士学位；1990年，毕业于惠灵顿维多利亚大学，获统计与运筹学硕士学位；1992年—1995年，任澳大利亚联邦科学院（CSIRO）海洋实验室统计师；1993年，毕业于澳大利亚国立大学，获统计学博士学位；1995年—2000年，任拉筹伯大学（La Trobe University）讲师、高级讲师（终身教职）；2000年—2003年，任新加坡国立大学副教授；2003年—2017年，任爱荷华州立大学（Iowa State University）统计系终身副教授、教授；2008年，任北京大学教授、讲席教授；2008年—2013年，任北京大学商务统计与经济计量系系主任；2010年，创立北京大学统计科学中心，任北京大学统计科学中心首届联席主任；2014年—2021年，任北京大学商务统计与经济计量系联合系主任；2021年8月1日，入选2021年中国科学院院士增选初步候选人名单；11月18日，当选中国科学院院士。2023年1月17日，当选第十四届全国政协委员。陈松蹊主要研究方向为超高维大数据统计分析、环境统计、非参数统计方法等。

陈松蹊与合作者提出了基于U-统计量和L2范数的超高维均值向量、协方差矩阵和回归系数的假设检验方法，突破了已有检验均要求数据维数和样本量是同阶的限制，在超高维下实现了对假设检验第一类错误概率的控制。在几个框架下建立了经验似然的一阶Wilks定理和二阶巴特莱特调整，为经验似然成为基本的非参数统计方法做出了贡献。

科研获奖

获奖时间	获奖项目名称	奖项
2017年	高维数据统计推断方法	教育部高校科学技术奖自然科学一等奖

科研项目

项目名称	批准号	项目类型	时间
高维数据统计建模与分析	1131002	国家自然科学基金重点项目	2012年—2016年
金融连续时间随机过程的统计推断	71371016	国家自然科学基金面上项目	2014年—2017年
大数据驱动的管理决策模型与算法	71532001	国家自然科学基金重点项目	2016年—2020年
空气质量统计诊断模型	2016YFC0207700	国家重点研发专项项目	2016年—2020年
面向儿童脑发育障碍性疾病的神经机制建模与辅助诊疗算法	12026607	数学与医疗健康交叉重点专项	2021年—2022年
面向管理决策大数据分析的理论与方法	92046021	国家自然科学基金重点项目	2021年—2022年
变系数流行病学模型的统计推断	12071013	国家自然科学基金面上项目	2021年—2024年
参考资料：

学术论文

据2024年1月北京大学光华管理学院网站显示，陈松蹊在学术杂志发表论文126篇。Web of Science H-指数 31，I-10指数56，总他引3127次。

Gu, J. and Chen, S.X. (2024) Distributed Statistical Inference under Heterogeneity, Journal of Machine Learning Research to appear .

Zheng，Xiangyu and Chen，S.X. （2023）Segmented Linear Regression Trees，Acta Mathematica Sinica，to appear.

Chen, Hanyue, Chen, S.X. and Mu Mu (2023). A Statistical Review on the Optimal Fingerprinting Approach in Climate Change Studies, Climate Dynamics, to appear.

Tong, P.F., Chen, S.X. and Tang, C.Y. (2023) Multivariate calibrations with auxiliary information, Statistica Sinica, to appear.DOI:10.5705/ss.202023.0151

Zheng, Xiangyu and Chen, S.X.(2023) Dynamic synthetic control method for evaluating treatment effects in auto-regressive processes.Journal of the Royal Statistical Society Series B: Statistical Methodology,00:1–22.

Chen, S.X., Qiu, Y.M. and S.Y. Zhang (2023) Sharp Optimality for High Dimensional Covariance Testing under Sparse Signals, The Annals of Statistics,51(5):1921-1945.

Tong, P.F., Zhan, H.X. and Chen, S.X. (2023) Ensembled Seizure Detection based on Small Training Samples, IEEE Transaction on Signal Processing,72: 1-14. DOI：10.1109/TSP.2023.3333546

Zhang, SY, S.X. Chen and Yumou Qiu (2023) Mean Tests For High-dimensional Time Series, Statistica Sinica, to appear.

Peifeng Tong, Wu Su, He Li, Jialin Ding, Haoxiang Zhan, Song Xi Chen (2023). Distribution Free Domain Generalization, Proceedings of the 40th International Conference on Machine Learning(ICML).

Ying Zhang, Song Xi Chen, Le Bao(2023). Air pollution estimation under air stagnation—A case study of Beijing,Environmetrics,34(6), e2819

Zhu Y, Gu J, Qiu Y, Chen SX. （2023）Real-World COVID-19 Vaccine Protection Rates against Infection in the Delta and Omicron Eras. Research，6，Article 0099.

Zhu，YR, Gu, J., Yumou Qiu, S.X. Chen (2023) Estimating COVID-19 Vaccine Protection Rates via Dynamic Epidemiological Models--A Study of Ten Countries, The Annals of Applied Statistics,17(4):3324–3348.

Chen，SX, Guo, B. and Qiu, YM (2023) Testing and Signal Identification for Two-sample High-dimensional Covariances via Multi-level Thresholding, Journal of Econometrics, 235, Issue 2, 1337-1354.

Tong, P. F., Chen, S. X., & Tang, C.Y. (2022). Detecting and evaluating dust-events in North China with ground air quality data. Earth and Space Science, 9, e2021EA001849

Luo, S., Zhu, Y., & Chen, S. X. (2022). Episode based air quality assessment. Atmospheric Environment, 285, 119242.

陈松蹊，毛晓军，王聪（2022）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.

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。

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.

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。

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。

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.

Zhu, Y.R.，Liang, Y.S. and Chen, S.X. (2021) Assessing Local Emission for Air Pollution via Data Experiments, Atmospheric Environment, 252, 118323.

Chen, S.X. and L-H Peng (2021) Distributive statistical inference for massive data, The Annals of Statistics, 49, 2851–2869.

Chang, J-Y., Chen, S.X., Tang, C-Y. and Wu, T-T (2021) High-dimensional empirical likelihood inference, Biometrika, 108, 127-147.

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

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

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.

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。

Zhang, S., Chen, S.X. and Lu, L. (2021), Inference for Variance Risk Premium, China Finance Review International, 11, 26-52.

Mao, X-J., Wong, R. K-W and Chen, S. X. (2021) Matrix Completion under Low-Rank Missing Mechanism, Statistica Sinica, 31, 2005-2030.

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.

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.

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.

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.

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.

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.

Zheng, XY and Chen, SX (2019) Partitioning Structure Learning for Segmented Linear Regression Trees, Advances in Neural Information Processing Systems (NeurIPS), 2019.

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

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.

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.

J. He and S. X. Chen (2018) High-Dimensional Two-Sample Covariance Matrix Testing via Super-diagonals, Statistica Sinica, 28, 2671-2696.

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.

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.

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.

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.

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.

Wang, Y., Tu, Y-D and S. X. Chen (2016) Improving inflation prediction with the quantity theory. Economics Letters, 149, 112-115.

Chen, S.X. (2016) 　Peter Hall's Contribution to the Bootstrap, The Annals of Statistics, 44, No. 5, 1821–1836.

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.

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.

He, J. and S. X. Chen (2016) Testing Super-Diagonal Structure in High Dimensional Covariance Matrices, Journal of Econometrics, 194, 283-297

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.

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.

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.

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.

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.

Chen, S.X. and Z. Xu (2013). On smoothing estimation for seasonal time series with long cycles, Statistics and Its Interface, 6, 435-447.

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.

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.

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.

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.

Li, J. and S. X. Chen (2012). Two Sample Tests for High Dimensional Covariance Matrices, The Annals of Statistics, 40, 908-940.

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.

Chen, S. X. and C. Y. Tang (2011). Nonparametric Regression with Discrete Covariates and Missing Value. Statistics and Its Interface, 4, 463-474.

J. Chang and S.X. Chen (2011). On the approximate maximum likelihood estimation for diffusion processes. The Annals of Statistics, 39, 2820-2851.

Chen, S. X. and C. Y. Tang (2011). Properties of Census Dual System Population Size Estimators. International Statistical Review, 79, 336-361.

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.

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.

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.

Chen, S. X. and P-S Zhong (2010). ANOVA for longitudinal data with missing values. The Annals of Statistics, 38, 3630-3659.

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.

Chen, S. X., Delaigle, A. and Hall, P. (2010). Nonparametric estimation for levy-type processes, Journal of Econometrics, 157, 257-271.

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.

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.

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.

Chen, S. X. and I. Van Keilegom (2009). A review on empirical likelihood for regressions (with discussions), Test, 3, 415-447 .

Chen, S. X. and Van Keilegom, I. (2009). Empirical likelihood test for a class of regression models. Bernoulli, 15, 955-976.

C. Y. Tang and S. X. Chen (2009). Parameter estimation and bias correction for diffusion processes. Journal of Econometrics, 149, 65—81.

Chen, S. X., L. Peng and Y-L, Qin (2009). Effects of Data Dimension on Empirical Likelihood, Biometrika, 96, 711–722.

Wang, D. and S.X. Chen (2009). Empirical Likelihood for Estimating Equation with Missing Values. The Annals of Statistics, 37, 490–517.

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.

Chen, S.X. and Chiumin Wong (2009). Smoothed Block Empirical Likelihood for Quantiles of Weakly Dependent Processes, Statist Sinica, 19, 71-82.

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.

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.

Chen, S.X: (2008). Nonparametric Estimation of Expected Shortfall. Journal of Financial Econometrics, 6, 87-107.

Chen, S. X. and T. Huang (2007). Nonparametric Estimation of Copula Functions for Dependent Modeling. Canadian Journal of Statistics, 35, 265-282.

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.

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.

Chen, S.X. and H.-J., Cui (2006). On Bartlett Correction of Empirical Likelihood in the Presence of Nuisance Parameters, Biometrika, 93, 215-220.

Chen, S.X. and Qin, J. (2006). An Empirical likelihood Method in Mixture Models with Incomplete Classifications, Statistica Sinica,16, 1101-1115.

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.

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.

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.

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.

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.

Chen, S. X. and Hall, P. (2003). Effects of bagging and bias correction on estimators defined by estimating equations, Statistica Sinica,13, 97-109.

Chen, S. X and Cui, H-J. (2003). An extended empirical likelihood for generalized linear models. Statistica Sinica, 13, 69-81.

Chen, S. X. and Hall, P. (2003). EFFECTS OF BAGGING AND BIAS CORRECTION ON ESTIMATORS DEFINED BY ESTIMATING EQUATIONS, Statistica Sinica, 13, 97-109.

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.

Chen, S. X, Yip, P. and Zhou, Y. (2002). Sequential line transect surveys. Biometrics, 58, 263-269.

Chen, S. X. (2002). Local linear smoothers using asymmetric kernels. Ann. Inst. Statist. Math., 54, 312-323.

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.

Chen, S. X. and Qin, Yong Song (2002). Confidence interval based on a local linear smoother. Scand. J. Statist., 29, 89-99.

Chen, S. X. and Cowling, A. (2001). Measurement Errors in Line Transect Surveys where Detection varies with Distance and Size. Biometrics, 57, 732-742.

Chen, S. X. and Qin, Yong Song (2000). Empirical Likelihood confidence interval for a local linear smoother. Biometrika, 87, 946-953.

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.

Chen, S. X. (2000). Gamma kernel estimators for density functions. Ann. Inst. Statist. Math. 52, 471-480.

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.

Chen, S. X. (2000). Beta kernel smoothers for regression curves. Statistica Sinica.10, 73-91.

Chen, S. X. (1999). Beta kernel estimators for density functions. Computational Statistics and Data Analysis, 31, 131-145.

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.

Chen, S. X. (1999). Estimation in independent observer line transect surveys for clustered populations. Biometrics, 55 , No. 3, 754-759.

Brown, B. M. and Chen, S. X. (1999). Beta-Bernstein smoothing for regression curves with compact support. Scand. J. Statist. . 26, 47-59.

Brown, B. M. and Chen, S. X. (1998). Combined Empirical Likelihood. Ann. Inst. Statist. Math, 50, 697-714.

Chen, S.X. (1998). Measurement errors in line transect surveys. Biometrics, 54, 899-908.

Chen, S.X. (1997). Empirical likelihood for nonparametric density estimation. Aust. J. Statist. , 39,47-56

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.

Chen, S.X. (1996). Empirical likelihood confidence intervals for nonparametric density estimation. Biometrika, 83, 329-341.

Chen, S.X. (1996). Studying school size effects in line transect sampling using the kernel method. Biometrics , 52, 1283-94.

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.

Chen, S.X. (1994). Comparing empirical likelihood and bootstrap hypothesis tests. J. Mult. Anal, 51, 277-293.

Chen, S.X. (1994). Empirical likelihood confidence intervals for linear regression coefficients. J. Mult. Anal. 49, 24-40.

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.

Chen, S.X. and Hall, P. (1993). Smoothed empirical likelihood confidence intervals for quantiles. Ann. Of Statistics, 21,1166-1181.

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.

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.

人才培养

主讲课程

陈松蹊主讲课程：高等多元统计分析、大样本统计理论。

培养的研究生

博士研究生：王莹（中国人民大学经济学院教师）、张澍一

硕士研究生：孙浩轩

科研态度

陈松蹊认为做研究一定要保持一个向上的心态，保持积极的心态，要有强烈的内驱力、有耐性。

寄语学生

陈松蹊

毕业生要确立更高的目标，同时正确看待人生中的曲折和弯路，享受不确定性带来的可能性和惊喜，在困难面前永不放弃，努力为推动社会进步贡献北师大人的智慧。

荣誉表彰

获奖时间	奖项名称
1989年	新西兰电信奖学金（Telecom New Zealand）奖学金
1990年—1992年	澳大利亚国立大学（Australian National University）博士奖
2008年	爱荷华州立大学（Iowa State University）教员杰出研究奖
2009年	美国统计学会会士
2021年11月18日	中国科学院院士
	美国科学促进会会士
	数理统计研究所会士

社会任职

编辑

时间	担任职务
2008年—2009年	国际华人统计学会理事会成员
2010年—2013年	《统计及其接口》（《Statistics and Its Interface》）联席主编
2010年—2019年	《统计年鉴》（《The Annals of Statistics》）编委
2013年—2018年	《商业与经济统计杂志》（《Journal of Business and Economic Statistics》）编委
2016年—2019年	国际数理统计学会理事会常务理事
2017年—	国家统计局咨询委员
2018年—2020年	《美国统计学会会刊》（《Journal of the American Statistical Association》）
2018年—	《环境》副主编
	中国统计学会常务理事
	伯努利学会科学书记
	第十四届全国政协委员

人物评价

编辑

陈松蹊从不停留在舒适区，而是会选择内心深处认为真正重要的问题，凭借着学术直觉与热情信念，全身心地投入到新理论与新领域的开拓中去。（北京大学评）

陈老师总是凭借着他的研究激情、克服问题的信念，全身心的投入以及天赋去解决一个接着一个的问题。（博士生闫晗评）

陈松蹊

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陈松蹊

陈松蹊

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