近期论文
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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 "model selection for generalized linear models with factor-augmented predictors", Applied Stochastic Models for Business and Industry, 25(3): 241-242.
2008
Huang, D., Wang, H., and Yao, Q. (2008), Estimating GARCH models: when to use what? Econometrics Journal, 11(1): 27-38.
Shao, J. and Wang, H. (2008), Confidence intervals based on survey data with nearest neighbor imputation, Statistica Sinica, 18(1): 281-297.
Wang, H., Ni, L., and Tsai, C. L. (2008), Improving dimension reduction via contour-projection, Statistica Sinica, 18(1): 299-311.
Wang, H. and Xia, Y. (2008), Sliced regression for dimension reduction (Technical Appendix), Journal of the American Statistical Association, 103(482): 811-821.
Luo, R., Wang, H., and Tsai, C. L. (2008), On mixture regression shrinkage and selection via the Mr. Lasso, International Journal of Pure and Applied Mathematics, 46: 403-414.
Wang, H. and Leng, C. (2008), A note on adaptive group lasso, Computational Statistics & Data Analysis, 52(12): 5277-5286.
Jiang, G. and Wang, H. (2008), Should earnings thresholds be used as delisting criteria in stock market? Journal of Accounting and Public Policy , 27(5): 409-419.
Luo, R. and Wang, H. (2008), A composite logistic regression approach for ordinal panel data regression, International Journal of Data Analysis Techniques and Strategies , 1(1): 29-43.
Leng, C. and Wang, H. (2008), Tuning parameter selection consistency in an ultrahigh dimensional setup: a comment on the sure independence screening rule, Journal of Royal Statistical Society , Series B, 70: 896-897.
2007
Wang, H., and Leng, C. (2007), Unified lasso estimation via least square approximation, Journal of American Statistical Association, 102(479): 1039-1048. (The R Code).
Wang, H., Li, R., and Tsai, C. L (2007), Tuning parameter selectors for the smoothly clipped absolute deviation method, Biometrika, 94(3): 553-568.
Wang, H., Li, G., and Tsai, C. L. (2007), Regression coefficients and autoregressive order shrinkage and selection via the lasso, Journal of Royal Statistical Society, Series B, 69(1): 63-78. (The Proof of Theorem 4)
Wang, H. (2007), A note on iterative marginal optimization: a simple algorithm for maximum rank correlation estimation, Computational Statistics and Data Analysis, 51(6): 2803-2812. (The Matlab Code).
Wang, H., Li, G., and Jiang, G. (2007), Robust regression shrinkage and consistent variable selection via the LAD-LASSO, Journal of Business & Economics Statistics, 25(7): 347-355.
Wang, H. and Chow, S. C. (2007), Sample size calculation for comparing means , Encyclopedia of Clinical Trials, Wiley. DOI: 10.1002/9780471462422.eoct006.
Wang, H. and Chow, S. C. (2007), Sample size calculation for comparing proportions , Encyclopedia of Clinical Trials, Wiley. DOI: 10.1002/9780471462422.eoct005.
Wang, H. and Chow, S. C. (2007), Sample size calculation for comparing variabilities, Encyclopedia of Clinical Trials, Wiley. DOI: 10.1002/9780471462422.eoct008.
Wang, H. and Chow, S. C. (2007), Sample size calculation for comparing time-to-event, Encyclopedia of Clinical Trials, Wiley DOI: 10.1002/9780471462422.eoct007.
2005
Wang, H., Chow, S. C., and Chen, M. (2005), A Bayesian approach on sample size calculation for comparing means , Journal of Biopharmaceutical Statistics, 15(5): 799-807.
2003
Chow, S.C., Shao, J., and Wang, H. (2003), Sample Size Calculations in Clinical Research. Chapman and Hall/CRC, New York, NJ, ISBN: 0824709705.
Chow, S.C., Shao, J., and Wang, H. (2003), In vitro bioequivalence testing, Statistics in Medicine, 22(1): 55-68.
Chow, S.C., Shao, J., and Wang, H. (2003), Statistical tests for population bioequivalence, Statistica Sinica, 13(2): 539-554.
Wang, H. and Shao, J. (2003), Two-way contingency tables under conditional hot deck imputation, Statistica Sinica, 13(3): 613-623.
Wang, H. and Chow, S.C. (2003), Imputation with item nonrespondents, Encyclopedia of Biopharmaceutical Statistics , 2nd Edition. Ed. Chow, S.C., Marcel Dekker, Inc., New York. 443-448.
Wang, H., Zhang, Y., Shao, J., and Chow, S.C. (2003), In vitro bioequivalence testing, Encyclopedia of Biopharmaceutical Statistics, 2nd Edition. Ed. Chow, S.C., Marcel Dekker, Inc. New York. 449-455.
Wang, H. (2003), Imputation in clinical research, Encyclopedia of Biopharmaceutical Statistics, 2nd Edition. Ed. Chow, S.C., Marcel Dekker, Inc. New York, New York. 437-442.
Wang, H., Cheng, B., and Chow, S.C. (2003), Sample size determination based on rank tests in clinical research, Journal of Biopharmaceutical Statistics, 13(4): 735-751.
Lee, Y., Wang, H., and Chow, S.C. (2003), Comparing variabilities in clinical research, Encyclopedia of Biopharmaceutical Statistics, 2nd Edition. Ed. Chow, S.C., Marcel Dekker, Inc. New York. 214-230.
2002
Shao, J. and Wang, H. (2002), Sample correlation coefficients based on survey data under regression imputation, Journal of American Statistical Association, 97(458): 544-552.
Wang, H. and Chow, S.C. (2002), A practical approaches for parallel trials without equal variance assumption, Statistics in Medicine, 21(20): 3137-3151.
Chow, S.C., Shao, J., and Wang, H. (2002), Individual bioequivalence testing under 2x3 designs, Statistics in Medicine, 21(5): 629-648.
Chow, S.C., Shao, J., and Wang, H. (2002), Probability lower bound for USP/NF test, Journal of Biopharmaceutical Statistics, 12(1): 79-92.
Wang, H. and Chow, S.C. (2002), On statistical power for average bioequivalence testing under replicated crossover design, Journal of Biopharmaceutical Statistics, 12(3): 295-309.
Chow, S.C., Shao, J., and Wang, H. (2002), A note on sample size calculation for mean comparisons based on non-central t-statistics, Journal of Biopharmaceutical Statistics, 12(4): 441-456.
Wang, H., Chow, S.C., and Li, G. (2002), On sample size calculation based on odds ratio in clinical trials, Journal of Biopharmaceutical Statistics, 12(4): 471-483.
Lee, Y., Shao, J., Chow, S.C., and Wang, H. (2002), Test for inter-subject and total variabilities under crossover design, Journal of Biopharmaceutical Statistics, 12(4): 503-534.
2001
Chow, S.C. and Wang, H. (2001), On sample size calculation in bioequivalence trials, Journal of Pharmacokinetics and Pharmacodynamics, 28(2): 155-169.
Wang, H. (2001), Two-way contingency tables with conditionally and marginally imputed data, Ph.D. thesis, University of Wisconsin-Madison.
中文论文发表
2018
王汉生， “朴素的数据价值观 ”，《新经济导刊》，2018年6月号 总第265期。
周静，沈俏蔚，涂平，王汉生（2017）， “原创还是转发？基于社交媒体UGC的交互效用研究”，《营销科学学报》，第13卷第4辑，55-67。
2017
周静，周小宇，王汉生（2017） “自我网络特征对电信客户流失的影响研究”，《管理科学》，第30卷第5期，28-37。
2015
林野，周静，王汉生（2015） “电视广告定价与社交收视率”，《统计学评论》，第9卷，93~103。
2014
王汉生（2014） “大数据概念被神化”，《新京报》，2014-06-27。
王汉生（2014） “从数据到价值”，《彭博商业周刊：中文版》。
2013
李季，周李超，王汉生（2013） “多产品协同促销模式下的零售商促销时间决策模型”，《中国管理科学》，第21（4）期，第89—97页。
2010
王汉生、张瀚宇、何天英、郭露茜（2010） “上市公司财务参数与其股价波动性关系探讨”，《证券市场导报》，总第211期，2010年，2月号，第74-77页。
姜国华，王汉生（2010） “取消ST制度，完善退市制度，促进股市健康发展”，《证券市场导报》，2010年，6月增刊，第42-48页。
黄达、王汉生（2010） “GARCH模型估计方法选择及对上证指数的应用”，《数理统计与管理》，第29卷，第3期，第544-549页。
2009
胡新杰、罗荣华、江明华、王汉生（2008） “基于高维0-1变量的EM 算法在移动通信客户细分中的应用”，《数理统计与管理》，2009，第28卷 第2期，第264-269页。
2008
岳衡、王汉生、姜国华（2008） “大股东资金占用与上市公司ST关系的研究”，《金融学季刊》，第4卷，第2期，第1-19页。。
李季、王汉生、涂平（2008） 对于尝试-重购新产品扩散模型的改进：logit模型及NILS估计 《中国管理科学》，第16卷，第6期，2008年12月。
2007
丁嘉丽、符国群、涂平、王汉生（2007） “消费者对不同强弱品牌的质量感知：评价模式的调节作用”，《数理统计与管理》，第26卷，第6期， 第977-983页。
姜国华、王汉生（2007） “ST：不怕烂货就怕假货”，《新财经》，2007年6月，第90页。
常莹、李季、王汉生、涂平（2007） “具备重复购买机制的新产品扩散模型：理论模型与非线性最小一乘估计”， 《营销科学学报》，第2卷，第4辑，第22-31页。
2006
姜国华、王汉生（2006） “审计作为证券市场有效监管工具之探讨”， 《中国注册会计师》，理论研究版，2006年10月号，第63-65页。
王汉生、江明华、曹丽娜、金英（2006） “超级市场零售商品的购物篮分析”， 《营销科学学报》，第2卷，第1辑，第71-77页。
胡健颖、姜国华、王汉生（2006） “实证研究中预测模型的选择：从逐步回归到信息标准”，《数理统计与管理》， 2006年1月，第25卷，第1期，第21-26页。
2005
姜国华、王汉生（2005） “上市公司两年亏损就应该被ST吗？”，《经济研究》，2005年，第3期，第100-107页。
王汉生、胡健颖（2005） “山西省商品房市场的发展规律”，《数理统计与管理》，第24卷，第2期，第7-13页。
王汉生、江明华、陈可（2005） “增加新功能产品的非线性定价研究”，《营销科学学报》，第1卷，第2辑，第132-137页。
2004
姜国华、王汉生（2004） “财物报表分析与上市公司ST预测研究”，《审计研究》，2004年，第6期，第60-63页。
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