个人简历

王汉生教授现任北京大学光华管理学院商务统计与经济计量系系主任。1998年北京大学数学科学学院，概率统计系，统计学本科，2001年美国威斯康星大学麦迪逊分校，统计学博士。
他发表英文学术论文五十余篇，中文论文近二十篇。合著英文专著1本，独立完成中文教材2本。先后担任多个学术刊物副主编(Associate Editor)。这些刊物包括：The Annals of Statistics (2008—2009)，Computational Statistics & Data Analysis (2008—2011),Statistics and its Interface (2010至今)，Journal of the American Statistical Association (2011至今), 以及Statistica Sinica (2011至今)。
教育背景
2001
威斯康辛大学
统计学
博士
1998
北京大学
统计学
学士
职业经历
2010~至今
光华管理学院商务统计与经济计量系 教授
2005~2010
光华管理学院商务统计与经济计量系 副教授
2003~2005
光华管理学院商务统计与经济计量系 助理教授
2002~2003
美国Forest Research Institute 统计师
2001~2002
美国StatPlus, Inc 统计师
最新观点
王汉生：数据思维，从数据分析到商业价值
王汉生教授研究报告：车联网数据与商业价值
王汉生：个人征信中的误差评估
王汉生：从搜索序列文本看高端商务车与商学院

研究领域

高维数据分析、变量选择、数据降维、极值理论、以及半参数模型。主要应用研究兴趣为：搜索引擎营销、社会关系网络"现主要理论研究兴趣为：高维数据分析、变量选择、数据降维、极值理论、以及半参数模型。主要应用研究兴趣为：搜索引擎营销、社会关系网络。"

近期论文

2019
Gao, Z., Ma, Y., Wang, H., and Yao, Q. Banded spatio-temporal autoregressions, Journal of Econometrics, 208(1): 211-230.
Zhu, X., Chang, X., Li, R., and Wang, H. Portal nodes screening for large scale social networks, Journal of Econometrics, To appear.
Chen, Y., Pan, R., Guan, R., and Wang, H. Analyzing Beijing point of interest data using group linked cox process, Statistics and Its Interface, To appear.
Zhu, X., Huang, D., Pan, R., and Wang, H. Multivariate spatial autoregression for large scale social networks, Journal of Econometrics, To appear.
Zhang, X., Pan, R., Guan, G., Zhu, X., and Wang, H. Network logistic regression model, Statistica Sinica, To appear.
Xu, K., Wang, J., Pan, R., and Wang, H. Photographic diary: A new estimation approach to pm2.5 monitoring, Statistics and Its Interface, To appear.
Sun, L., Zheng, X., Jin, Y., Jiang, M., and Wang, H. Estimating promotion effects using big data: A partially profiled LASSO model with endogeneity correction, Decision Sciences, To appear.
Zhou, J., Zhou, J., Ding, Y., and Wang, H. The magic of danmaku: A social interaction perspective of gift sending on live streaming platforms, Electronic Commerce Research and Applications, To appear.
Zhou, J., Li, D., Pan, R., and Wang, H. Network GARCH model, Statistica Sinica, To appear.
Sun, Z., Wang, H. Network imputation for spatial autoregression model with incomplete Data, Statistica Sinica, To appear.
Ma, Y., Pan, R., Zou, T., and Wang, H. A naive least squares method for spatial autoregression with covariates, Statistica Sinica, To appear.
Zhu, X., Wang, W., Wang, H., and Wolfgang Karl Hardle Network quantile autoregression, Journal of Econometrics, To appear.
Chang, X., Huang, D., and Wang, H. A popularity scaled latent space model for large-scale directed social network, Statistica Sinica, To appear.
2018
Lan, W., Fang, Z., Wang, H., and Tsai, C. L. (2018), Covariance matrix estimation via network structure, Journal of Business and Economics Statistics, 36(2): 359-369.
Huang, M., Wang, S., Wang, H., and Jin, T. (2018), Maximum smoothed likelihood estimation for a class of semiparametric pareto mixture densities, Statistics and Its Interface, 11(1):31-40.
Xu, K., Sun, J., Liu, J., and Wang, H. (2018), An empirical investigation of taxi driver response behavior to ride-hailing requests: A spatio-temporal perspective, Plos One, 13(6):e0198605.
Pan, R., Guan, R., Zhu, X., and Wang, H. (2018), A latent moving average model for network regression, Statistics and Its Interface, 11(4): 641-648.
Huang, D., Guan, G., Zhou, J., and Wang, H. (2018), Network-based naive Bayes model for social network, Science China Mathematics, 61 (4): 627-640.
Zhou, J., Huang, D., and Wang, H. (2018), A note on estimating network dependence in a discrete choice model, Statistics and its Interface, 11(3): 433-439.
Huang, D., Chang, X., and Wang, H. (2018), Spatial autoregression with repeated measurements for social networks, Communications in Statistics - Theory and Methods, 47(15): 3715-3727.
Huang, D., Zhou, J., and Wang, H. (2018), RFMS method for credit scoring based on bank card transaction data, Statistica Sinica, 28(4): 2903-2919.
Huang, M., Wang, S., Wang, H., and Jin, T. (2018), Maximum smoothed likelihood estimation for a class of semiparametric Pareto mixture densities, Statistics and Its Interface, 11(1), 31-40.
Cai, W., Guan, G., Pan, R., Zhu, X., and Wang, H. (2018), Network linear discriminant analysis, Computational Statistics and Data Analysis, 117: 32-44.
Lan, W., Ma, Y., Zhao, J., Wang, H., and Tsai, C. L. (2018), Sequential model averaging for high dimensional linear regression models, Statistica Sinica, 28(1): 449-469.
2017
Zhou, J., Huang, D., and Wang, H. (2017), A Dynamic Logistic Regression for Network Link Prediction, Science China Mathematics, 60(1): 165-176.
Zhou, J., Tu, Y., Chen, Y., and Wang, H. (2017), Estimating spatial autocorrelation with sampled network data, Journal of Business & Economic Statistics, 35(1): 130-138.
Zhu, X., Pan, R., Li, G., Liu, Y., Wang, H.,et al. (2017), Network vector autoregression, The Annals of Statistics, 45(3): 1096-1123.
Zou, T., Lan, W., Wang, H., and Tsai, C. L. (2017), Covariance regression analysis, Journal of the American Statistical Association, 112(517): 266-281.
2016
Huang, D., Yin, J., Shi, T., and Wang, H. (2016), A statistical model for social network labeling, Journal of Business and Economics Statistics, 34(3): 368-374.
Yan, T., Qin, H., and Wang, H. (2016), Asymptotics in undirected random graph models parameterized by the strengths of vertices, Statistica Sinica, 26(1): 273-293.
Pan, R., Wang, H., and Li, R. (2016), Ultrahigh dimensional multi-class linear discriminant analysis by pairwise sure independence screening, Journal of the American Statistical Association, 111(513): 169-179.
Lan, W., Zhong, P. S., Li, R., Wang, H., and Tsai, C. L.(2016), Testing a single regression coefficient in high dimensional model, Journal of Econometrics, 195(1): 154-168.
2015
Zhu, X., Huang, D., Pan, R., and Wang, H. (2015), An EM algorithm for click fraud detection, Statistics and its Interface, 9(3): 389-394.
Lu, X., Zhao, J., Chen, Y., and Wang, H. (2015), A choice model with a diverging choice set for POI data analysis, Statistics and its Interface, 9(3): 355-363.
Pan, R., Wang, H. (2015), A note on testing conditional independence for social network analysis, Science China: Mathematics, 58(6), 1179-1190.
Ma, Y., Lan, W., and Wang, H. Testing predictor significance with ultra high dimensional multivariate responses, Computational Statistics and Data Analysis, 83: 275-286.
Lan, W., Luo, R., Tsai, C.L., Wang, H., and Yang, Y. (2015), Testing the diagonality of a large covariance matrix in a regression setting, Journal of Business and Economics Statistics, 33(1): 76-86.
Ma, Y., Lan, W., and Wang, H. (2015), A high dimensional two sample test under a low dimensional structure, Journal of Multivariate Analysis, 140: 162-170.
2014
Huang, D., Li, R., and Wang, H. (2014), Feature screening for ultrahigh dimensional categorical data with applications, Journal of Business and Economics Statistics, 32(2): 237-244.
Huang, M., Li, R., Wang, H., and Yao, W. (2014), Estimating mixture of gaussian processes by kernel smoothing, Journal of Business and Economics Statistics, 32(2): 259-270.
Lan, W., Wang, H., and Tsai, C.L. (2014), Testing covariates in high dimensional regression, Annals of Institute of Statistical Mathematics, 66(2): 279-301.
Guan, G., Guo, J., and Wang, H. (2014), Varying naive Bayes models with application to classification of Chinese text documents , 32(3): 445-456.
2013
Zhao, J., Leng, C., Li, L., and Wang, H. (2013), High dimensional influence measure, The Annals of Statistics, 41(5): 2639-2667.
Zhang, Q., Li, D., and Wang, H. (2013), A note on tail dependence regression, Journal of Multivariate Analysis, 120: 163-172.
Jiang, Q., Wang, H., Xia, Y., and Jiang, G. (2013), On a principal varying coefficient model, Journal of the American Statistical Association, 108(501): 228-236.
An, B., Wang, H., and Guo, J. (2013), Testing the statistical significance of an ultra-high dimensional naive Bayes classifier, Statistics and Its Interface, 2013: 223-229.
An, B., Wang, H., and Guo, J. (2013), Multivariate regression shrinkage and selection by canonical correlation analysis, Computational Statistics and Data Analysis, 6(2): 223--229.
2012
Wang, H. (2012), Factor profiled sure independence screening, Biometrika, 99(1): 15-28.
Lan, W., Wang, H., and Tsai, C.L. (2012), A Bayesian information criterion for portfolio selection, Computational Statistics & Data Analysis, 56(1): 88-99.
Liang, H., Wang, H., and Tsai, C.L. (2012), Profiled forward regression for ultrahigh dimensional variable screening in semiparametric partially linear models, Statistica Sinica, 22(2): 531-554.
2011
Zhang, Q. and Wang, H. (2011), On BIC's selection consistency for discriminant analysis, Statistica Sinica, 21(2): 731-740.
Pan, R., Wang, H., and Tsai, C.L. (2011), Regression analysis of asymmetric pairs in large scale network data, Communication in Statistics, 40(10): 1540-1547.
Li, J., Pan, R., and Wang, H. (2010), Selection of best keywords: A Poisson regression model， Journal of Interactive Advertising, 11(1): 27-35.
2010
Yin, J., Geng, Z., Li, R., and Wang, H. (2010), Nonparametric covariance model, Statistica Sinica , 20(1): 469-479.
Tsai, C. L., Wang, H., and Zhu, N. (2010), Does a Bayesian approach generate robust forecasts? evidence from applications in portfolio investment decisions, Annals of the Institute of Statistical Mathematics, 62(1): 109-116.
Guan, Y. and Wang, H. (2010), Sufficient dimension reduction for spatial point processes directed by Gaussian random fields, Journal of Royal Statistical Society, Series B, 72(3): 367-387.
Zhang, H. H., Lu, W., and Wang, H. (2010), On sparse estimation for semiparametric linear transformation models , Journal of Multivariate Analysis, 101(7): 1594-1606.
2009
Wang, H. (2009), Forward regression for ultra-high dimensional variable screening , Journal of the American Statistical Association, 104(488): 1512-1524.
Wang, H., Li, B., and Leng, C. (2009), Shrinkage tuning parameter selection with a diverging number of parameters, Journal of Royal Statistical Society, Series B, 71(3): 671-683.
Leng, C. and Wang, H. (2009), On general adaptive sparse principal component analysis , Journal of Computational and Graphical Statistics, 18(1): 201-215.
Wang, H. (2009), Rank reducible varying coefficient model, Journal of Statistical Planning and Inference , 139(3): 999-1011.
Su, X., Tsai, C. L., Wang, H., Nickerson, D. M., and Li, B. (2009), Subgroup analysis via recursive partitioning, Journal of Machine Learning Research, 10: 141-158.
Wang, H. and Xia, Y. (2009), Shrinkage estimation of the varying coefficient model, Journal of the American Statistical Association, 104(486): 747-757.
Wang, H. and Tsai, C. L. (2009), Tail index regression , Journal of the American Statistical Association, 104(487): 1233-1240.
Luo, R., Wang, H., and Tsai, C. L. (2009), Contour projected dimension reduction, The Annals of Statistics, 37(6): 3743-3778.
Wang, H. and Tsai, C. L. (2009), A discussion on \
现为国际统计协会会员（International Statistical Institute），美国统计学会(American Statistical Association)，美国数理统计研究员(Institute of Mathematical Statistics)，英国皇家统计协会(Royal Statistical Society)，以及泛华统计学会(International Chinese Statistical Association)会员。