1. Yin, C., Ai, M., Chen, X., Kong, X. (2022). Empirical likelihood for generalized linear models with longitudinal data. Journal of Systems Science and Complexity, accepted on Jan 27, 2022.
2. Kong, X., Yuan, M. and Zheng, W. (2021). Approximate and exact designs for total effects. Annals of Statistics, 3(49): 1594–1625.
3. Kong, X. and Zheng, W. (2020). Design based incomplete U-statistics. Statistica Sinica, 3(32): 1593–1618.
4. Huang, Y., Kong, X. and Ai, M. (2019). Optimal designs for the Lasso in sparse linear models. Metrika, 83: 255–273.
5. Yu, J., Kong, X., Ai, M. and Tsui, K. L. (2018). Optimal designs for dose–response models with linear effects of covariates. Computational Statistics & Data Analysis, 127: 217–228.
6. Kong, X., Ai, M. and Tsui, K. L. (2018). Design for sequential follow-up experiments in computer emulations. Technometrics, 60(1): 61–69.
7. Kong, X., Ai, M. and Tsui, K. L. (2018). Flexible sliced designs for computer experiments. Annals of the Institute of Statistical Mathematics, 70(3): 631–646.