- CHEN Songxi
- Chair Professor
- Phone :86-10-62760736
Ph.D., Australian National University, 1993.
M.S., Victorria Uinversity of Wellington, 1990.
M.S., Beijing Normal University, 1988.
B.S., Beijing Normal University, 1983.
Mathematical Statistics: High Dimensional Statistical Inference, Empirical Likelihood, Inference for Stochastic Processes.
Environmental Statistics: Air Quality Assessment, Climate Change Effects.
l 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.
l 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.
l Zheng, XY& and Chen, SX (2019) Partitioning Structure Learning for Segmented Linear Regression Trees, Advances in Neural Information Processing Systems (NeurIPS), 2019.
l 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.
l Xu, Ziping&, Song Xi Chen, Xiaoqing Wu(2020) Meteorological Change and Impacts on Air Pollution Results from North China, Journal of Geophysics Research-Atmosphere, to appear
l 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.
l 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.
l Chang, J& and S.X. Chen (2011). On the approximate maximum likelihood estimation for diffusion processes. The Annals of Statistics, 39, 2820-2851.
l 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.
l 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.
& student co-authors