Publications
[Google Scholar Citations][ORCID][ResearchGate]
Selected Manuscripts
Zhang, F., Fan, C., and Li, D. (2024). Measuring Forecast Accuracy for Expectile Regression with Possible Model Misspecification. Manuscript, Submitted.
Wu, J., Zhang, B., Li, D., and Zheng, Z. (2023). Simultaneous Heterogeneous and Reduced-Rank Learning for Multivariate Response Regression. Manuscript, Under review.
Li, D., Bao, Y., Li, L, and Pan, J. (2023). Semiparametric Estimation of Mean and Variance in Generalized Estimating Equations. Manuscript, 2nd round review.
Peer-Reviewed Publications
Li, D., Kong, Y., and Zerom, D. (2024). Nonparametric Screening for Additive Quantile Regression in Ultra-high Dimension. Journal of Nonparametric Statistics, Accepted. [PDF] [Journal link][Supplementary Material][R Code]
Yu, J., Li, D., Luo, L., and Zhao, H. (2024). Reproducible Learning for Accelerated Failure Time Models via Deep Knockoffs. Communications in Statistics - Theory and Methods, 53, Pages 6544-6560 (published online: 25 Aug 2023). [PDF][Journal link]
Chen, Q., He, Y., Hu, M., and Li, D.(2023). (Em)powering the Underdog: How Power States Enhance Referral Intention-Behavior Consistency for Underdog Entrepreneurs. Journal of Business Research, 169, Article 114300. [Journal link]
Li, D., Yu, J., and Zhao, H. (2023). CoxKnockoff: Controlled Feature Selection for the Cox Model Using Knockoffs. Stat, 12(1), e607. [The Lay Abstract][PDF][Supplementary Material][Journal link][Python Code]
Li, D., Kong, Y., Fan, Y., and Lv, J. (2022). High-dimensional interaction detection with false sign rate control. Journal of Business & Economic Statistics, 40, Pages 1234-1245.[PDF][Supplementary Material][Journal link]
Zhang, J., Li, D., Xia, Y., and Liao, Q. (2022). Bayesian Aerosol Retrieval-Based PM2.5 Estimation through Hierarchical Gaussian Process Models. Mathematics, 10(16), Article 2878.[PDF][Journal link]
Zhou, J., Li, Y., Zheng, Z., and Li, D. (2022). Reproducible learning in large-scale graphical models. Journal of Multivariate Analysis, 189, Article 104934.[PDF][Journal link]
Dong, Y., Li, D., Zheng, Z., and Zhou, J. (2022). Reproducible feature selection in high-dimensional accelerated failure time models. Statistics & Probability Letters, 181, Article 109275.[PDF][Supplementary Material][Journal link]
Dong, R., Li, D., Zheng, Z. (2021). Parallel integrative learning for large-scale multi-response regression with incomplete outcomes. Computational Statistics & Data Analysis, 160, Article 107243. [PDF][Journal link]
Zheng, Z., Zhu, J., Guo, X., and Li, D. (2018). Recovering the Graphical Structures via Knockoffs. Procedia Computer Science, 129, Pages 201-207. [PDF][Journal link]
Widjaja, R. F., Panamtash, H., Zhou, Q., and Li, D. (2018). Solar power forecasting with model selection analysis. Proceedings of 2018 Clemson University Power Systems Conference. DOI: 10.1109/PSC.2018.8664060. [PDF][Journal link]
Gu, H., Li, D., Liu, C., and Rao, Z. (2018). %ggBaseline: a SAS macro for analyzing and reporting baseline characteristics automatically in medical research. Annals of Translational Medicine, 6(16), 326. [PDF][Journal link]
Kong, Y., Li, D., Fan. Y., and Lv, J. (2017). Interaction Pursuit in High-Dimensional Multi-response Regression via Distance Correlation. The Annals of Statistics, 45, Pages 897-922. [PDF][Supplementary material][Journal link]
Fan, Y., Kong, Y., Li, D., and Zheng, Z. (2015). Innovated Interaction Screening for High-Dimensional Nonlinear Classification. The Annals of Statistics, 43, Pages 1243-1272. [PDF][Supplementary material][Journal link]
Li, D. and Pan, J. (2013). Empirical Likelihood for Generalized Linear Models with Longitudinal Data. Journal of Multivariate Analysis, 114, Pages 63-73. [PDF][Journal link]
Zhou, Y., Wu, G., and Li, D. (2006). A kernel-type estimator of a quantile function under randomly truncated data. Acta Mathematica Scientia, 26, Pages 585-594. [PDF][Journal link]
Zhou, Y. and Li, D. (2006). Confidence Intervals of Variance Functions in Generalized Linear Model. Acta Mathematicae Applicatae Sinica, 22, Pages 353-368. [PDF][Journal link]
Book Chapter
- Li, D., Kong, Y., Zheng, Z., and Pan, J. (2022). Recent Advances in Big Data Analytics. In The Palgrave Handbook of Operations Research (Editors: Saïd Salhi and John Boylan). [PDF]. Book available from Springer.