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].9999js金沙老品牌学报: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].9999js金沙老品牌学报: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].9999js金沙老品牌学报,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].9999js金沙老品牌学报, 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.
【会议论文】
Lu, S.,Wang, S*., Wang, H. PLSGLR-based Approach for Risk Analysis on Peer-to-peer Internet Finance Platforms in China. The 9th International Conference on PLS and Related Methods. 2017 June Macau.
Zhou Jiantao, Ai Jing,Wang Shanshanand Wang Tianyang.Economic and Non-economic Losses Claim Effects on the Severity of Opportunistic Fraud in Auto Bodily Injury Compulsory Liability (BICL) Insurance: Evidence from China.7th China International Conference on Insurance and Risk Management (CICIRM),2016,,358-397
【Selected Presentations】
The 2019 IMS-China International Conference on Statistics and Probability, Dalin, China
The 9thInternational Conference on PLS and Related Methods, Macau, China 2017
International Conference on Energy Finance, Hangzhou, 2017
The 10thICSA International Conference, Shanghai, 2016
International Workshop on Advances in Data Science, Beijing, 2016
The 2thInternational Symposium on Interval Data Modelling: Theory and Applications, Xiamen, 2016
The1stInternational Conference onBig Data & Applied Statistics,Beijing, 2014
The16thand 17th5.4 Youth Meeting of Probability and Statistics in Beijing-Tianjin Area, Beijing, 2012 and 2013
The 9thAnnual Probability and Statistics, Tianjin, 2010