- .1.Tingting Huang, Saporta Gilbert, Huiwen Wang, Shanshan Wang*. A Robust Spatial Autoregressive Scalar-on-Function Rregression with t-distribution. Advances in Data Analysis and Classification, 2020, Published online: https://doi.org/10.1007/s11634-020-00384-w
- .2.Wang Huiwen, Liu Ruiping, Wang Shanshan*. Ultra-high dimensional variable screening via Gram–Schmidt orthogonalization. Computational Statistics, 2020, 35, 1153-1170
- .3.Xiaokang Wang, Huiwen Wang, Shanshan Wang*, Jidong Yuan. Convex Clustering Method for Compositional Data via Sparse Group Lasso, Neurocomputing, 2020, accepted (21 Oct 2020)
- .4.Zhichao Wang, Huiwen Wang, Shanshan Wang*, Shan Lu, Gilbert Saporta. Linear mixed-effects model for longitudinal complex data with diversified characteristics,Journal of Management Science and Engineering, 2020, 5(2), 105-124
- .5.Zhichao Wang, Huiwen Wan, Shanshan Wang*. Linear Mixed-Effects Model for Multivariate Longitudinal Compositional Data. Neurocomputing, 2019,335: 48-58.
- .6.Huiwen Wang, Zhichao Wang & Shanshan Wang* . Sliced inverse regression method for multivariate compositional data modeling, Statistical Papers,2019, Published online: https://doi.org/10.1007/s00362-019-01093-z
- .7.Wang Huiwen, Gu Jie, Wang Shanshan*, Gilbert Saporta. Spatial partial least squares autoregression: Algorithm and applications, Chemometrics and Intelligent Laboratory Systems, 2019,184: 123-131
- .8.Wang Shanshan, Xiang Liming*. Penalized empirical likelihood inference for sparse additive hazards regression with a diverging number of covariates. Statistics and Computing, 2017, 27(5): 1347-1364.
- .9.Wang Shanshan, Xiang Liming*. Two-layer EM-algorithm for ALD mixture regression models: A new solution to composite quantile regression. Computational Statistics & Data Analysis, 2017, 115:136-154.
- .10.Wang Shanshan, Cui Hengjian*. Partial penalized empirical likelihood ratio test under sparse case. Acta Mathematica Applicatae Sinica (English Series), 2017, 32(2): 327-344