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  • Ph.D. Statistics, Michigan State University, 2005
  • B.S. Statistics, University of Science & Techology of China, 2000

Research Interests

  • Nonparametric and semiprametric models
  • Large sample theory
  • Network data analysis
  • Functional data analysis
  • Medical imaging 

Selected Publications

  • Xue,L. and Yang, L. (2006) Estimation of semiparametric additive coefficient model. Journal of Statistical Planning and Inference,136, 365-368.
  • Xue, L. and Yang, L. (2006)  Additive coefficient modelling via polynomial spline. Statistica Sinica,16, 1423-1446.
  • Yang, L., Park, B. U., Xue, L. and H ̈ardle, W. (2006) Estimation and testing for varying coefficients in additive models with marginal integration. Journal of the American Statistical Association,101, 1212-1227.
  • Xue, L. (2009),  Variable selection in additive models.  Statistica Sinica, 19, 1281-1296.
  • Xue, L., Wang, L., and Qu, A. (2010)  Incorporating correlation for multivariate failure time data when cluster size is large. Biometrics, 66, 393-404.
  • Xue, Land Liang, H. (2010) Polynomial spline estimation for the generalized additive coefficient model. Scandinavian Journal of Statistics,37, 26-46.
  • Xue, L.and Wang, J. (2010) Distribution function estimation by constrained polynomial spline regression. Journal of Nonparametric Statistics22, 443-457
  • Xue, L., Qu, A., and Zhou, J. (2010) Consistent model selection for marginal generalized additive model for correlated data. Journal of the American Statistical Association, 105, 1518-1530.
  • Xue, L.and Qu, A. (2012) Variable selection in high-dimensional varying-coefficient models with global optimality. Journal of Machine Learning Research,13, 1973-1998.
  • Jiang, S. and Xue, L. (2013) Lag selection in stochastic additive models.Journal of Nonparametric Statistics,25, 129-146. (Laha Award paper) 
  • Wang, L., Xue, L., Qu, A. and Liang, H. (2014)  Estimation and model selection in generalized additive partial linear models for correlated data with diverging number of covariates. Annals of Statistics, 42, 592-624.
  • Wang, L. and Xue, L. (2015) Constrained polynomial spline estimation of monotone additive models. Journal of Statistical Planning and Inference167,  27-40.
  • Jiang, S. and Xue, L. (2015) Globally consistent model selection in semi-parametric additive coefficient models. Journal of Nonparametric Statistics27,  532-551.
  • Yang, M., Xue, L., and Yang, L. (2016) Variable selection for additive model via cumulative ratios of empirical strengths total. Journal of Nonparametric Statistics, 3, 595-616.
  • Zheng, X.,Xue, L.and Qu, A. (2018) Time-varying correlation structure estimation and local-feature detection for spatio-temporal data. Journal of Multivariate Analysis,168, 221-239.
  • Tekwe, C., Zoh, R., Yang, M., Carroll, R. J., Honvoh, G. A., Allison, D. B, Benden, M., and Xue, L.(2019) Instrumental variable approach to estimating the functional linear regression model with an imprecisely measured covariate. Statistics in Medicine38, 3764-3781.
  • James, A.,Xue, L.and Lesser, V. (2019) Information criterion for nonparametric model-assisted survey estimators, Journal of Survey Statistics and Methodology7398-421. (SRMS travel award paper)
  • Yang, M., Hua, Z.,Xue, L. and Hu, M. (2019) Zmaxtest for delayed effect in immuno-oncology clinical trials. Journal of Biopharmaceutical Statistics10, 1-23.
  • Xue, L., Shu, X. and Qu, A. (2020) Dynamic model selection of time-varying network. Statistica Sinica,30, 251-284.
  • Xue, L., Shu, X., Shi, P., Wu, C. and Qu, A. (2020) Time-varying feature selection 

    for longitudinal analysis. Statistics in Medicine39, 156-170.

  • Wang, L.,Xue, L., and Yang, L. (2020) Estimation of additive frontier functions with shape constrains. Journal of Nonparametric Statistics32, 262-293.
  • Fang, Y.,Xue, L., Martins-Filho C. and Yang, L. (2022) Robust Estimation of Additive Boundaries With Quantile Regression and Shape Constraints. Journal of Business and Economic Statistics40, 615-628.
  • Tekwe, C., Zhang, M., Carroll, R., Luan, Y.,Xue, L, Zoh, R., Allison, D., Geraci, M. (2022) Estimation of sparse functional quantile regression with measurement error: A SIMEX approach. Biostatistics23, 1218-1241.
  • Zhang, M.,Xue, L., Carmen, T., Bai, Y. and Qu, A. (2023) Partially functional linear quantile regression with measurement errors. Statistica Sinica, To appear.

Instructional and Departmental Activities

  • ST 625 Generalized Regression Models II
  • ST 662 Advanced Theory of Statistics II
  • ST 663 Advanced Theory of Statistics III

Professional Service

  • Associate Editor, Sankhya Series B, 2012-2016
  • Associate Editor, Biostatistics and Epidemiology, 2017-current
  • Associate Editor, Statistica Sinica, 2020-current
  • Associate Editor, JASA (Theory and Methods), 2023-current
  • ASA Oregon Chapter, Treasurer, Vice President, and President, 2020-2023
  • ASA Excellent in Statistical Reporting Award Commitee, Chair, 2020-2022
  • Local Organization Committee Member, IISA Conference, 2016
  • Local Organization Committee Co-chair, Infinite Possibilities Conference, 2015
  • Program Committee, 2015 Joint Statistics Meetings, 2014-2015
  • Organizer, Workshop onNonparametric Estimation and Functional data, 2014
  • Program Committee, Joint Applied Statistics Symposium of ICSA and KISS, 2014