在研论文

1. An improved bayesian information criterion for high dimensional analysis.
2. Bootstrapped empirical likelihood.

发表论文

1. Chao, Y., Ma, X. , & Zhu, B. (2024) Distributed optimal subsampling for quantile regression with massive data. Journal of Statistical Planning and Inference, 233, 106186.
2. Chao, Y., Huang, L. Ma, X. , & Sun, J. (2024) Optimal subsampling for modal regression in massive data. Metrika. 87，379-409.
3. Ma, X. , & Zhang, P. (2023). Quantile regression for compositional covariates. Communications in Statistics-Simulation and Computation, 52(3),658-668.
4. Shen, L. Chao, Y., & Ma, X. (2023). Distributed quantile regression in decentralized optimization. Information Sciences, 643, 119259.
5. Ma, X. , Du, Y., & Wang, J. (2022). Model detection and variable selection for mode varying coefficient model. Statistical Methods & Applications. 31, 321–341
6. Ma, X. , Wang, S & Zhou, W. (2022). Statistical inference in massive datasets by empirical likelihood. Computational Statistics. 37, 1143–1164. R code: DACEL
7. Liu, P., Ma, X., & Zhou, W. (2022). High order conditional distance covariance with conditional mutual independence. Probability in the Engineering and Informational Sciences, 36(1), 126-143.
8. Chao, Y., Ma, X. , Li, Y, & Huang, L. (2022). A penalized estimation for the Cox model with ordinal multinomial covariates. Journal of Statistical Computation and Simulation, 92(6), 1194-1223.
9. Ma, X. , Wang, S., & Zhou, W. (2021). Testing multivariate quantile by empirical likelihood. Journal of Multivariate Analysis, 182, 104705.
10. Wang, L, Ma, X. & Zhang, J. (2020). Feature screening for ultrahigh-dimensional additive logistic models. Journal of Statistical Planning and Inference. 205, 306-317.
11. Chen, X, Ma, X. & Zhou, W. (2020). Kernel density regression. Journal of Statistical Planning and Inference. 205, 318-329
12. Li, X., Ma, X. & Zhang, J. (2018). Conditional quantile correlation screening procedure for ultrahigh-dimensional varying coefficient models. Journal of Statistical Planning and Inference, 197, 69-92.
13. Chen, Y., Ma, X. & Zhou, J. (2018). Variable selection for mode regression. Journal of Applied Statistics 45(6): 1077–1084.
14. Chen, X., Ma, X. Wang, X. & Zhang, J. (2017). Efficient feature screening for ultrahigh-dimensional varying coefficient models. Statistics and Its Interface, 10(3), 407-412.
15. Li, X., Ma, X. & Zhang, J. (2017). Robust feature screening for varying coefficient models via quantile partial correlation. Metrika, 80(1): 17–49.
16. Ma, X. , Chen, X. & Zhang, J. (2017). Fast robust feature screening for ultrahigh-dimensional varying coefficient models. Journal of Statistical Computation and Simulation, 87(4), 724-732.
17. Ma, X. & Zhang, J. (2016). Robust model-free feature screening via quantile correlation. Journal of Multivariate Analysis, 143, 472-480. R package QCSIS .
18. Ma, X. & Zhang, J. (2016). A new variable selection approach for varying coefficient models. Metrika, 79(1), 59-72.
19. Ma, X., He, X. & Shi, X. (2016). A variant of K nearest neighbor quantile regression. Journal of Applied Statistics, 43(3), 526-537.
20. Ma, X. & He F. (2014). Power weighted quantile regression and its application. Journal of Data Science, 12(3): 535-544.
21. 方福前, 马学俊(2016). 中国经济减速的原因与出路. 中国人民大学学报, 6: 64–75. (新华文摘,2017, 4: 44-50.)
22. 马学俊, 胡小宁, 赵晋文(2016). Logistic半参数变系数模型的变量选择. 统计与决策, 7: 76–77.
23. 马学俊(2015). GSIS超高维变量筛选. 统计与信息论坛, 30(8):16–19.
24. 马学俊, 史小康(2015). 次序响应变量模型及其应用. 统计与决策, 12: 71–73.
25. 马学俊, 何晓群, 马曼(2015). 消费、投资和出口对经济增长的影响研究— 基于变系数模型. 现代管理科学, 7: 64–66.
26. 马学俊, 贾立文(2015). 经济发展、城镇化对铁矿石需求的影响研究. 中国物价, 7: 40–43.