Past Papers (2010-2019)

2019

• Narisetty, N.N., Shen, J., and He, X. (2019) Skinny Gibbs: A Consistent and Scalable Gibbs Sampler for Model Selection. Journal of the American Statistical Association , Vol. 114, no. 527, 1205-1217.

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• Yuan, C., Guo, W., He, X., and Guo, J. (2019). A mixture factor model with applications to microarray data. Test , Vol. 28, no. 1, 60-76.

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• Giessing, A. and He, X. (2019). On the Predictive Risk in Misspecified Quantile Regression. Journal of Econometrics, Vol. 213, no. 1, 235-260.

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• Van Pelt KL, Cameron KL, Campbell DE, D`Lauro CJ, He X, Houston MN, Jackson JC, Johnson BR, McGinty G, Meehan S, O`Donnell PG, Pasquina P, Peck KY, Svoboda SJ, McAllister T, McCrea M, Broglio SP. (2019). A cohort study to identify and evaluate concussion risk factors across multiple injury settings: findings from the CARE Consortium. Injury Epidemiology , 6(1), 1-11.

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• Eckner, J.T., Wang, J., Nelson, L.D., Bancroft, R., Pohorence, M., He, X., Broglio, S.P., Giza, C.C., Guskiewicz, K.M., Kutcher, J.S., McCrea, M. (2019+). Effect of routine sport participation on short-term clinical neurological outcomes: A comparison of non-contact, contact, and collision sport athletes. Sports Medidine , to appear. doi: 10.1007/s40279-019-01200-y

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2018

• Yang, X., Narisetty, N.N., and He, X. (2018) A new approach to censored quantile regression estimation. Journal of Computational and Graphical Statistics, Vol, 27, no 2. 417-425.

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• Zheng, Q., Peng, L., and He, X. (2018). High dimensional censored quantile regression. Annals of Statistics , Volume 46, no. 1, 308-343.

Previous

• Alsalaheen, B., Stockdale, K., Pechumer, D., Giessing, A., He, X., and Broglio, S.P. (2017). Cumulative Effects of Concussion History on Baseline Computerized Neurocognitive Test Scores. Systematic review and meta-analysis. Sports Health , Vol. 9, Issue 4, 324-332. https://doi.org/10.1177/1941738117713974

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• Feng, X. and He, X. (2017). Robust Low-rank Data Matrix Approximations. Science China: Mathematics , Vol. 60, no. 2, 189-200.

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• Shen, J., Wang, Y., and He, X. (2017). Penalized likelihood for logistic-normal mixture models with unequal variances. Statistica Sinica , Vol. 27, 711-731.

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• Park, S., He, X., and Zhou, S. (2017). Dantzig-type penalization for multiple quantile regression with high dimensional covariates. Statistica Sinica , Vol. 27, 1619-1638. https://doi.org/10.5705/ss.202016.0081

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• Park, S. and He, X. (2017). Hypothesis testing for regional quantiles. Journal of Statistical Planning and Inference , Vol. 191, 13-24.

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• He, X. (2017). A Conversation with Roger Koenker. International Statistics Review , Vol. 85, no. 1, 46-60.2016

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• Yang, Y., Wang, H.X., and He, X. (2016). Posterior inference in Bayesian quantile regression with asymmetric Laplace likelihood (with discussion). International Statistics Review , Vol. 84, no. 3,327-344. (Rejoinder pp. 367-370)

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• Zhang, S. and He, X. (2016). Inference based on adaptive grid selection of probability transforms. Statistics , Vol. 50 (3), 667-688.

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• Ma, S. and He, X. (2016). Inference for Single-index Quantile Regression Models with Profile Optimization. Annals of Statistics , Vol. 44, No. 3, 1234-1268.

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• Broglio, S., Rettmann, A., Greer, J., Brimacombe, S., Moore, B., Narisetty, N., He, X., and Eckner, J. (2016). Investigating a novel measure of brain networking following sport concussion. International Journal of Sports Medicine , Vol. 37(9), 714-722.

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• Eckner, J. T., Rettman, A., Narisetty, N.N., Greer, J., Moore, B., Brimacombe, S., He, X., Broglio, S. P. (2016). Stability of an ERP-Based Measure of Brain Network Activation in Athletes: A New Electrophysiological Assessment Tool for Concussion. Brain Injury , Vol. 30(9), 1075-1081.

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• Lefton-Greif, M.A., Perlman, A.L., He, X., Lederman, H.M., Crawford, T.O. (2016). Assessment of Impaired Coordination between Respiration and Deglutition in Children and Young Adults with Ataxia Telangiectasia. In review at Developmental Medicine & Child Neurology , Vol. 58(10), 1069-1075.2015

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• Feng, Y., Chen, Y., and He, X. (2015). Bayesian quantile regression with approximate likelihood. Bernoulli , Vol. 21, no. 2, 832 - 850.

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• Shen, J., and He, X. (2015). Inference for Subgroup Analysis with a Structured Logistic-Normal Mixture Model. Journal of the American Statistical Association, Volume 110, 303-312.

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• Yang, Y., and He, X. (2015). Quantile Regression for Spatially Correlated Data: an Empirical Likelihood Approach. Statistica Sinica , vol. 25, no. 509, 261-274.

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• Narisetty, N.N., and He, X. (2015). Discussion of ``multivariate functional outlier detection''. Statistical Methods & Applications , Vol. 24, 209-215. DOI: 10.1007/s10260-015-0305-z

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• Zheng, Q., Peng, L., and He, X. (2015). Globally adaptive quantile regression with ultra-high dimensional data. Annals of Statistics , Vol. 43, no. 5, 2225 -- 2258.2014

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• Narisetty, N.N., and He, X. (2014). Bayesian Variable Selection with Shrinking and Diffusing Priors. Annals of Statistics , Vol. 42, no. 2, 789-817.

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• Zheng, S., Jiang, D., Bai, Z.D., and He, X. (2014). Inference on multiple correlation coefficients with moderately high dimensional data. Biometrika , vol. 101, no. 3, 748-754.

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• Shen, J., and He, X. (2014). Generalized F Test and Generalized Deviance Test in Two-way ANOVA Models for Randomized Trials. Journal of Biopharmaceutical Statistics , Vol. 24, no. 3, 523-534.

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• Feng, X., and He, X. (2014). Statistical inference based on robust low-rank data matrix approximation. Annals of Statistics , Vol. 42, no. 1, 1-224.2013

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• Dalpiaz, D., He, X., and Ma, P. (2013). Bias Correction in RNA-Seq Short-read Counts using Penalized Regression. Statistics in Biosciences , Vol. 5, Issue 1, 88-99. DOI: 10.1007/s12561-012-9057-6

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• He, X., Wang, L., and Hong, H. G. (2013). Quantile-adaptive Model-free Variable Screening for High-dimensional Heterogeneous Data. Annals of Statistics , Vol. 41, no. 1, 342-369.

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• Kim, J.Y., and He, X. (2013). Robust EM Clustering via Mixture Model for Multivariate Regression (Invited Paper) Quantitative Bio-Science , Vol. 32(2), 69-80.2012

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• Li, B., Liang, F., He, X., and Hu, J. (2012). Reno: Regularized Nonparametric Analysis of Protein Lysate Array Data. Bioinformatics , Vol. 28, Issue 9, 1223-1229.

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• Hu, J., and He, X. (2012). Searching for Alternative Splicing with a Joint Model on Probe Measurability and Expression Intensities. Journal of the American Statistical Association , Vol. 107, no. 499, 935-945.

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• Yang, Y., and He, X. (2012). Bayesian empirical likelihood for quantile regression. Annals of Statistics , Volume 40, no. 2 , 1102-1131.

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• Tang, Y., Wang, H., He, X., and Zhu, Z.Y. (2012). An informative subset-based estimator for censored quantile regression. Test , Vol. 21, no. 4, 635-655.

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• He, X., Yang, Y., and Zhang, J. (2012). Bivariate downscaling with asynchronous measurements. JABES , Vol. 17, no. 3, 476-489.

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• Wang, H. X., Li, D., and He, X. (2012). Estimation of High Conditional Quantiles for Heavy-tailed Distributions. Journal of the American Statistical Association , Vol. 107, no. 500, 1453-1464.

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• Lin, G., He, X., and Portnoy, S.L. (2012). Quantile Regression with Doubly Censored Data. Computational Statistics & Data Analysis , Vol. 56, Issue 4, 797-812. doi:10.1016/j.csda.2011.03.0092011

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• Yang, J.Y. and He, X. (2011). A Multi-step Protein Lysate Array Quantication Method and its Statistical Properties. Biometrics , Vol. 67(4), 1197-1205. DOI: 10.1111/j.1541-0420.2011.01567.x

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• Li, C., Wei, Y., Chappell, R. J. and X. He (2011), Bent Line Quantile Regression with application to an allometric study of land mammals' speed and mass. Biometrics , vol. 67, 242-249.

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• Wang, X., Guo, J., and He, X. (2011). Finding the minimal set for collapsible graphical models. Proceedings of the American Mathematical Society , Vol. 139, 361-373.

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• Guo, J., Xu, P.F., and He, X. (2011). An Improved Iterative Proportional Scaling Procedure for Gaussian Graphical Models. Journal of Computational and Graphical Statistics , Vol. 20, 417-432.

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• Liu, R. Y., Tao, J., Shi, N.Z., and He, X. (2011). Bayesian analysis of the patterns of biological susceptibility via reversible jump MCMC sampling. Computational Statistics & Data Analysis, Volume 55, Issue 3, 1498-1508.

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• Malandraki, G., McCullough, G., He, X., McWeeny, E., and Perlman A. (2011). Teledynamic Evaluation of Oropharyngeal Swallowing. Journal of Speech, Language, and Hearing Research , Vol.54, 1497-1505. doi:10.1044/1092-4388(2011/10-0284)

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• Feng, X., He, X., and Hu, J. (2011). Wild bootstrap for quantile regression. Biometrika , Vol. 98, no. 4, 995-999. doi: 10.1093/biomet/asr0522010

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• He, X., Hsu, Y. H., and Hu, M. (2010). Detection of Treatment Effects by Covariate-adjusted Expected Shortfall. Annals of Applied Statistics , Vol. 4, No. 4, 2114-2125.

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• Broglio, S. P., Schnebel, B., Sosnoff, J.J., Shin, S., Feng, X., He, X., Zimmerman, J. (2010). The biomechanical properties of concussions in high school football. Medicine & Science in Sports & Exercise , Vol. 42(11), 2064-2071.

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• Hong, H. G., and He, X. (2010). Prediction of Functional Status for the Elderly Based on a New Ordinal Regression Model. Journal of the American Statistical Association , Vol. 105, No. 491: 930-941.

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• He, X. and Zhou, J. (2010). Discussion of "Envelope models for parsimonious and efficient multivariate linear regression", Statistica Sinica , Vol. 20, No. 3, 971-978.

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• He, X., Xue, H., and Shi, N.Z. (2010). Sieve Maximum Likelihood Estimation for Doubly Semiparametric Zero-Inflated Poisson Models. Journal of Multivariate Analysis , Volume 101, Issue 9, 2026-2038.