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TingtingHuang, Saporta Gilbert,HuiwenWang,ShanshanWang*. A Robust Spatial Autoregressive Scalar-on-Function Rregression with t-distribution.Advances in Data Analysis and Classification, 2021,15(1):57-81
Xiaokang Wang, Huiwen Wang,Shanshan Wang*, Jidong Yuan.Convex Clustering Method for Compositional Data via Sparse Group Lasso, Neurocomputing,2021,425:23-36
Huiwen Wang, Zhichao Wang &Shanshan Wang* . Sliced inverse regression method for multivariate compositional data modeling,Statistical Papers,2021,62(1):361-393
Wang Huiwen, Liu Ruiping,Wang Shanshan*. Ultra-high dimensional variable screening via Gram–Schmidt orthogonalization.Computational Statistics,2020,35:1153-1170
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
Zhichao Wang, Huiwen Wan
,Shanshan Wang*. Linear Mixed-Effects Model for Multivariate Longitudinal Compositional Data.Neurocomputing,2019,335: 48-58.
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
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.
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.
Wang Shanshan, Cui Hengjian*. Partial penalized empirical likelihood ratio test under sparse case.Acta Mathematica Applicatae Sinica (English Series), 2017, 32(2): 327-344
Jie Gu, Lihong Wang, Huiwen Wang,Shanshan Wang*. A novel approach to intrusion detection using SVM ensemble with feature augmentation.Computers & Security, 2019, 86:53-62
Yu Yang, Zou Zhihong,Wang Shanshan*. Statistical regression modeling for energy consumption in wastewater treatment.Journal of Environmental Sciences, 2019, 75: 201-208.
Haitao Zheng, Jie Hu,Shanshan Wang*, Huiwen Wang. Examining the influencing factors of CO2 emissions at city level via panel quantile regression: evidence from 102 Chinese cities.Applied Economics, 2019, 51(35): 3906-3919.
Wang Huiwen, Huang Tingting,Wang Shanshan*. A Flexible Spatial Autoregressive Modelling Framework for Mixed Covariates of Multiple Data Types,Communications in Statistics-Simulation and Computation, 2019, DOI:10.1080/03610918.2019.1626885
Yuan Wei, Huiwen Wang,Shanshan Wang*, Saporta, Gilbert. Incremental modelling for compositional data streams.Communications in Statistics- Simulation and Computation,2019, 48(8):2229-2243
Wang Shanshan, Hu Tao*, Cui Hengjian. Adjusted empirical likelihood inference for additive hazards regression.Communication in Statistics-Theory and Methods, 2016, 45(24):7294-7305
Wang Shanshan, Cui Hengjian. Empirical Likelihood Inference for Partially Linear Errors in Variables models with covariate data missing at random.Acta Mathematica Applicatae Sinica (English series), 2016, 32(2), 305-318.
Wang Shanshan, Cui Hengjian*, Li, Runze. Empirical Likelihood Inference for Semi-parametric Estimating Equations.Science China Mathematics, 2013, 56: 1247–1262.
Wang Shanshan,Cui Hengjian*. Partial Penalized Likelihood Ratio Test under Sparse Case.Statistics,2013.
Liu Ruiping, Wang Huiwen,Wang Shanshan*. Functional variable selection via Gram- Schmidt orthogonalization for multiple functional linear regression.Journal of Statistical Computation and Simulation, 2018, 88(18): 3664-3680
Yang Yu, Zhihong Zou,Shanshan Wang*. Bayesian quantile regression and variable selection for partial linear single-index model: Using free knot spline,Communications in Statistics - Simulation and Computation,2018,48(5),1429-1449
Wang Huiwen, Gu Jie,Wang Shanshan*. An effective intrusion detection framework based on SVM with feature augmentation.Knowledge-Based Systems, 2017,136:130-139.
Wei Yuan,Wang Shanshan*, Wang Huiwen. Interval-valued data regression using partial linear model.Journal of Statistical Computation and Simulation, 2017, 87(16): 3175-3194
Zhou Jiantao,Wang Shanshan*, Zhou Jianbo, Xu Yanli. Measurement of the severity of opportuneistic fraud in personal injury insurance: evidence from China.Emerging Markets Finance and Trade, 2017, 53(2): 387-399
Wang Shanshan, Zhao Tianhao, Zheng Haitao*, Hu Jie. The STIRPAT Analysis on Carbon Emission in Chinese Cities: An Asymmetric Laplace Distribution Mixture Model.Sustainability, 2017, 9(12), 2237
Yu Yang, Zou Zhihong,Wang Shanshan, Renate Meyer*. Bayesian non-parametric modelling of the link function in the single-index model using a Bernstein-Dirichlet process prior.Journal of Statistical Computation and Simulation, 2019, 89(17): 3290-3312
Peng Mengjiao, Xiang Liming*,Wang Shanshan. Semiparametric regression analysis of clustered survival data with semi-competing risks,Computational Statistics & Data Analysis, 2018, 124:53-70
Zheng Haitao, Hu Jie, Guan Rong* andWang Shanshan. Examining Determinants of CO2 Emissions in 73 Cities in China.Sustainability,2016,8(12), 1296.
Wang H, Zhang Y, Lu S andWang S*. Tracking and forecasting milepost moments of the epidemic in the early-outbreak: framework and applications to the COVID-19.F1000Research,2020, 9:333
王珂瑶,王惠文,赵青,王珊珊*.一种修正的马氏距离判别法[J/OL].北京航空航天大学学报:1-9[2021-07-09].
赵青,王惠文,王珊珊*.基于中心-对数半长的区间数据主成分分析[J/OL].北京航空航天大学学报:1-11[2021-07-09].
赵宪铎,王惠文,王珊珊*.带空间结构的人工神经网络建模方法[J].北京航空航天大学学报,2021,47(01):115-122.
刘瑞平,王惠文,王珊珊*.基于Gram-Schmidt变换的有监督变量聚类[J/OL].北京航空航天大学学报, 2019, 45(10):1-9
王惠文*,王玉茹,任若恩,夏棒，王珊珊.实物资金流量表的预测方法研究[J].管理科学学报, 2018, 21(09):6-16.
王珊珊,韩丽娟*,崔恒建,杨华.基于大气降水的华北地区土壤湿度预测模型[J].应用气象学报, 2011, 22(4):445-452.
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