在自己比较熟悉的统计包括纯计量领域,从文章角度来说,感觉光华的苏良军老师在计量上比较厉害,这几年的成果也不间断,journal of Econometrics,Econometrical theory等期刊文章不少,可能还缺少Econometrica这种顶级的文章。另外就是光华的王汉生老师,他是统计学的,从这四五年的文章来看,好像国内统计领域还没有人能达到他的水准,07年到09年短短三年的顶级刊物文章可能是国内统计牛人一辈子无法达到的水平,何况王老师还那么年轻,也就三十出头吧,(98年北大数学本科毕业,01年Wisconsin统计博士毕业)呵呵,前途不可限量,估计最近几年杰青啦长江啦的应该有戏。有时候也和别人讨论,国内一些四五十岁的统计牛人理论功底也都很厉害,但是他们到四五十这个年龄发一两篇JASA,annals of statistics这类期刊都觉得相当厉害了。但是看看国外经常有毕业不到三五年的统计博士,这类期刊都五六篇了。看来还是做得东西不够前沿或者学术氛围不行,没有站到前沿阵地上,原创性的东西不多,把大部分精力都放在跟在别人屁股后面修修补补了。另外国内做研究如果不和国际大牛合作,可能即使有好的论文也经常被歧视,被退稿。
王老师的成果目录,每次看到都要仰慕一次,感慨人和人差别怎么这么大呢?呵呵。人比人起死人,不管土鳖还是海龟,都要好好努力,只要自己感到内心充实,对研究保持兴趣,自己努力做些有意义的论文,其实这就是一种快乐。
2010
- Yin, J., Geng, Z., Li, R., and Wang, H. (2010) Nonparametric covariance model, Statistica Sinica . 20, 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, 109--116.
- Zhang, Q. and Wang, H. (2010) On BIC's Selection Consistency for Discriminant Analysis, Statistica Sinica, To Appear.
- 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, To appear.
- Zhang, H. H., Lu, W., and Wang, H. (2010) On sparse estimation for semiparametric linear transformation models , Journal of Multivariate Analysis, To appear.
- Wang, H. (2009) Forward regression for ultra-high dimensional variable screening Journal of the American Statistical Association. 104, 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, 671--683.
- Leng, C.and Wang, H. (2009). On general adaptive sparse principal component analysis Journal of Computational and Graphical Statistics, 18, 201-215.
- Wang, H. (2009) Rank reducible varying coefficient model, Journal of Statistical Planning and Inference . 139, 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, 747--757.
- Wang, H. and Tsai, C. L. (2009) Tail index regression Journal of the American Statistical Association, 104, 1233--1240.
- Luo, R., Wang, H., and Tsai, C. L. (2009) Contour projected dimension reduction, The Annals of Statistics, 37, 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, 241--242.
- Huang, D., Wang, H., and Yao, Q. (2008) Estimating GARCH models: when to use what?. Econometrics Journal, 11, 1-12.
- Shao, J. and Wang, H. (2008) Confidence intervals based on survey data with nearest neighbor imputation. Statistica Sinica, 18, 281-297.
- Wang, H., Ni, L., and Tsai, C. L. (2008). Improving dimension reduction via contour-projection. Statistica Sinica, 18, 299-311.
- Wang, H. and Xia, Y. (2008). Sliced regression for dimension reduction (Technical Appendix) Journal of the American Statistical Association, 103, 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, 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, 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, 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.


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