英文文章
1. Wang, G., Li, W. and Zhu, K.(2019). New HSIC-based tests for independence
between two stationary multivariate time series. Forthcoming in Statistica
Sinica, doi:10.5705/ss.202018.0159
2. Wang, G., Liang, B., Wang, H., Zhang, B. and Xie, B. (2019). Dimension
reduction for functional regression with a binary response. Forthcoming in
Statistical Papers,https://doi.org/10.1007/s00362-019-01083-1
3. Wang, G. and Lian, H. (2018). Functional Sliced Inverse Regression in a Repro-
ducing Kernel Hilbert Space: a Theoretical Connection to Functional Linear Re-
gression. Forthcoming in Statistical Sinica, doi:10.5705/ss.202017.0277
4. Wang, G., Zhang F. and Lian, H.(2020). Directional regression for functional
data.Journal of Statistical Planning and Inference 204,1-17.
5. Wang, G. and Song, X. (2018). Functional Sufficient Dimension Reduction for
Functional Data Classification. Journal of Classification 35,250-272.
6. Zhou, Y., Wang, G., Zhang, J. and Li, H.(2017). A hypothesis testing based
method for normalization and differential expression analysis of RNA-Seq data.
PloS ONE, 12.
7. Wang, G. (2017). Dimension reduction in functional regression with categorical
predictor. Computational Statisitcs, 32, 585-609.
8. Wang, G., Zhou, J., Wu, W. and Chen, M. (2017). Robust functional sliced
inverse regression. Statistical Papers, 58, 227-245.
9. Wang, G., Su, Y. and Shu, L. (2016). One-day-ahead daily power forecasting
of photovoltaic systems based on partial functional linear regression models.
Renewable Energy, 96, 469-478.
10. Wang, G., Feng, X. and Chen, M. (2016). Functional partial linear single-index
model. Scandinavian Journal of Statistics, 43, 261-274.
11. Wang, G., Zhou, Y., Feng, X. and Zhang, B. (2015). The hybrid method of F-
SIR and FSAVE for functional effective dimension reduction. Computational
Statistics & Data Analysis, 91, 64-77.
12. Feng, X., Wang, G., Wang, Y. and Song, X. (2015). Structure detection of
semiparametric structural equation models with Bayesian adaptive group lasso.
Statistics in Medicine, 34, 1527-1547.
13. Wang, G., Lin, N. and Zhang, B. (2014). Functional k-means inverse regres-
sion. Computational Statistics & Data Analysis, 70, 172-182.
14. Wang, G., Lin, N. and Zhang, B. (2013). Functional contour regression. Jour-
nal of Multivariate Analysis, 116, 1-13.
15. Wang, G., Lin, N. and Zhang, B. (2013). Dimension reduction in functional
regression using mixed data canonical correlation analysis. Statistics and Its
Interface, 6, 187-196.
16. Wang, G., Lin, N. and Zhang, B. (2012). Functional linear regression after
spline transformation. Computational Statistics & Data Analysis, 56,
587-601.
中文文章（*为指导学生）
1. 蒋勇，王国长，吴武清（2014）.股指期货的价格发现机制：基于结构变点分析框架.财政科学， 6，1-11.

2.高桃璇(*)，陈铭(*)，王国长（2018）.基于函数型数据的中国经济区划分.数理统计与管理，37，669-681.

3.丁辉，许文超，朱汉兵，王国长，张涛，张日权(2018). 函数型数据回归分析综述. 应用概率统计，34，630-654.

4.王国长，梁焙婷(*)，王金枝(*)(2019). 改进的自适应Lasso方法在股票市场中的应用. 数理统计与管理，38，750-760.

5.王国长，高桃璇(*)，徐世荣(*)(2019).  基于 Sparse-Group Lasso 的指数跟踪. 系统科学与数学 已接收。