High Dimensional Hypothesis Testing
Key Words: Covariance structure, Joint limiting law, Sparse alternative, Dense alternative, Intermediate limiting law, Uniform convergence.
  • Srinivasan, A., Xue, L. and Zhan, X. (2018)
    Compositional Knockoff Filter for FDR Control in Microbiome Regression Analysis.
    Technical Report, Penn State University.
  • Li. D., Xue, L. and Zou, H. (2018)
    Applications of Peter Hall's Martingale Limit Theory to Estimating and Testing High Dimensional Covariance Matrices.
  • Statistica Sinica, in press.
  • Li. D. and Xue, L. (2015+)
    Joint Limiting Laws for High-Dimensional Independence Tests. (arXiv, pdf, bib)
  • Technical Report, Penn State University.
Dimension Reduction and Latent Variable Models with Applications to Accounting, Economics and Finance
Key Words: Cross-sectional data; Approximate factor model; Sliced inverse regression; Forecasting.
  • Zou, H. and Xue, L. (2018)
    A Selective Overview of Sparse Principal Component Analysis.
    Technical Report, University of Minnesota and Penn State University.
  • Xue, L., Yao, J. and Yu, X. (2018)
    Revisiting Sufficient Forecasting: Nonparametric Estimation and Predictive Inference.
    [Winner of 2018 ASA Business and Economic Statistics Distinguished Student Paper Award]
    Technical Report, Penn State University.
  • Du, K., Huddart, S. J., Xue, L. and Zhang, Y. (2018)
    Using a Hidden Markov Model to Measure Reporting Systems. (ssrn)
    Technical Report, Penn State University.
  • Ke, Z., Xue, L. and Yang, F. (2017+)
    Diagonally-Dominant Principal Component Analysis
    Technical Report, University of Chicago and Penn State University.
  • Luo, W., Xue, L. and Yao, J. (2017+)
    Inverse Moment Methods for Sufficient Forecasting using High-Dimensional Predictors. (arXiv, pdf, ssrn, bib)
    Technical Report, Penn State University.
  • Fan, J., Xue, L. and Yao, J. (2017)
    Sufficient Forecasting Using Factor Models. (website, arXiv, pdf, ssrn, bib)
    Jounral of Econometrics, 201: 292-306.
Graphical and Network Models
  • Agarwal, A., Lee, K. and Xue, L. (2018)
    Temporal Exponential-Family Random Graph Models with Time-Evolving Latent Block Structure for Dynamic Networks.
    Technical Report, Penn State University.
  • Agarwal, A. and Xue, L. (2018)
    Model-Based Clustering of Nonparametric Weighted Networks with Application to Water Pollution Analysis.
    [Winner of 2018 ASA Risk Analysis Distinguished Student Paper Award]
    Technical Report, Penn State University.
  • Lyu, Y., Xue, L., Zhang, F., Koch, H., Saba, L., Kechris, K. and Li, Q. (2018)
    Condition-Adaptive Fused Graphical Lasso (CFGL): an Adaptive Procedure for Inferring Condition-Specific Gene Co-Expression Network.
    Technical Report, Penn State University.
  • Kim, B., Lee, K., Xue, L. and Niu, X. (2017+)
    A Review of Dynamic Network Models with Latent Variables.
    Technical Report, Penn State University.
  • Lee, K. and Xue, L. (2017)
    Nonparametric Mixture of Gaussian Graphical Models. (arXiv, pdf, bib)
    [Winner of 2016 ICSA Distinguished Student Paper Award]
    Technical Report, Penn State University.
  • Lee, K., Xue, L. and Hunter, D. (2017)
    Model-Based Clustering of Dynamic Networks.
    [Winner of 2016 ASA Statistical Learning and Data Science Distinguished Student Paper Award]
    Technical Report, Penn State University.
  • Ma, S., Xue, L. and Zou, H. (2013)
    Alternating Direction Methods for Latent Variable Gaussian Graphical Model Selection. (website, arXiv, pdf, software, bib)
    Neural Computation, 25: 2172-2198.
  • Xue, L., Zou, H. and Cai, T. (2012).
    Nonconcave Penalized Composite Conditional Likelihood Estimation of Sparse Ising Models. (website, arXiv, pdf, bib)
    [Winner of 2011 ENAR Distinguished Student Paper Award]
    The Annals of Statistics, 40(3): 1403-1429.
  • Xue, L. and Zou, H. (2012).
    Regularized Rank-Based Estimation of High-Dimensional Nonparanormal Graphical Models. (website, arXiv, pdf, bib)
    The Annals of Statistics, 40(5): 2541-2571.
Variable Selection and Feature Screening
  • Fan, J., Xue, L. and Zou, H. (2014)
    Strong Oracle Optimality of Folded Concave Penalized Estimation. (website, arXiv, pdf, bib)
    The Annals of Statistics, 42: 819-849.
  • Xue, L. and Zou, H. (2011).
    Sure Independence Screening and Compressed Random Sensing. (website, pdf, bib)
    Biometrika, 98(2): 371-380.
Large Covariacne Matrix Estimation
  • Fan, J., Xue, L. and Zou, H. (2016)
    Multi-Task Quantile Regression Under the Transnormal Model. (website, bib)
    Journal of the American Statistical Association, 111: 1726-1735.
  • Xue, L. and Zou, H. (2014).
    Rank-based Tapering Estimation of Bandable Correlation Matrices. (website, pdf, bib)
    Statistica Sinica, 24: 83-100.
  • Xue, L. and Zou, H. (2013).
    Minimax Optimal Estimation of General Bandable Covariance Matrices. (website, pdf, bib)
    Journal of Multivariate Analysis, 116: 45-51.
  • Xue, L. and Zou, H. (2013).
    Invited Discussion of "Large Covariance Estimation by Thresholding Principal Orthogonal Complements". (website, pdf, bib)
    Journal of the Royal Statistical Society: Series B, 75: 672-674
  • Xue, L., Ma, S. and Zou, H. (2012).
    Positive-Definite L1-Penalized Estimation of Large Covariance Matrices. (website, arXiv, pdf, bib)
    Journal of the American Statistical Association, 107: 1480-1491.
  • Xue, L. and Zou, H. (2012).
    Invited Discussion of "Minimax Estimation of Large Covariance Matrices under L1-Norm". (website, pdf, bib)
    Statistica Sinica, 22(4): 1349-1354
Interdisciplinary Research
  • Chen, Y., Ju, L., Zhou, F., Liao, J., Xue, L., Yuan, Y., Lu, H., Jackson, S. and Zhu C. (2018).
    An Integrin αIIbβ3 Intermediate Affinity State Mediates Biomechanical Platelet Aggregation.
    Technical Report, Georgia Institute of Technology.
  • Lin, N., Jing, R., Wang, Y., Yonekura, E., Fan, F. and Xue L. (2017).
    A Statistical Investigation of the Dependence of Tropical Cyclone Intensity Change on the Surrounding Environment. (website, pdf, bib)
    Monthly Weather Review, 145, 2813-2831.
  • Ju, L., Chen, Y., Xue, L., Du, X. and Zhu C. (2016).
    Cooperative Unfolding of Distinctive Mechanoreceptor Domains Transduces Force into Signals. (website, pdf, bib)
    [Featured in NSF Science360, Georgia Tech News and Penn State News]
    eLife, e15447.
  • Ye, L., Geng, Z., Xue, L. and Liu, Z. (2007).
    A Novel Real Time Method of Signal Strength Based Indoor Localization.
    Lecture Notes in Computer Science, 4705, 678-688.
  • Ye, L., Liu, Z., Xue, L., He. P. and Geng, Z. (2007).
    A Gradually Locating Method of Indoor Locating Estimation Based on Likelihood.
    Mobility Conference: Singapore, 91-97.
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