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冯龙

学位: 博士

毕业院校: 南开大学

邮件: flnankai@nankai.edu.cn

办公地点: 范孙楼126B

电话:

出生年月:

个人资料

  • 部门: 统计与数据科学学院
  • 性别:
  • 出生年月:
  • 专业技术职务: 副教授
  • 研究标签:
  • 毕业院校: 南开大学
  • 学位: 博士
  • 学历:
  • 联系电话:
  • 电子邮箱: flnankai@nankai.edu.cn
  • 办公地址: 范孙楼126B
  • 通讯地址:
  • 邮编: 300071
  • 传真:

工作经历

2014年7月--2019年6月 东北师范大学 讲师

2019年7月--2021年7月 东北师范大学 副教授

2021年12月--至今    南开大学    副教授、特聘研究员


教育经历

2005年9月---2009年6月  南开大学      数学试点班

2009年9月---2014年6月  南开大学      硕博连读  (导师:王兆军教授) 

2015年1月---2016年1月  佛罗里达大学     博士后   (导师:邱培华教授)


个人简介

 

冯龙现任南开大学统计与数据科学学院副教授、特聘研究员、博士生导师。2022年入选南开大学百名青年学科带头人。冯龙于本科毕业于南开大学数学科学学院陈省身数学试点班,博士毕业于南开大学数学科学学院概率论与数理统计专业,获得南开大学优秀博士论文奖。主要从事质量控制、非参数模型、高维数据分析、高频数据分析方面的研究。曾获得2012年教育部学术新人奖,于2012-2014年分别访问香港浸会大学、新加坡国立大学和香港大学,2015年于美国佛罗里达大学做博士后研究。在统计学国际顶尖杂志Journal of American Statistical AssociationBiometrikaAnnals of StatisticsJournal of EconometricsJournal of Business and Economic StatisticsTechnometrics等发表SCI论文30余篇。曾主持一项国家自然科学基金青年项目,正主持一项国家自然科学基金面上项目,南开大学百青项目一项。


研究领域

高维数据分析、计量经济学、图像数据质量控制等


教学工作

2022年春季学期  极限理论(概率论II) 本科生课程

2022年秋季学期   数理统计        本科生课程


科研项目

2016年1月--2018年12月  国家自然科学基金青年项目 超高维数据中若干检验问题的研究

2015年1月--2016年12月   东北师范大学校内青年基金  高维数据中若干检验问题的研究

2022年1月--2025年12月   南开大学校级人才科研经费  高维数据检验中的若干问题研究


论文专著

代表作:

1. Feng Long, Zou Changliang and Wang Zhaojun. (2016). Multivariate-sign-based high-dimensional tests for the two-sample location problem, Journal of American Statistical Association. 111, 721-735.

2. Feng Long, Jiang tiefeng, Liu Binghui and Xiong wei. (2021) Max-sum tests for cross-sectional dependence in high-dimensional panel data models. Annals of Statistics. Accepted.

3. Zou Changliang, Peng Liuhua, Feng Long andWang Zhaojun (2014). Multivariate-signs based high-dimensional tests for sphericity. Biometrika101(1), 229-236.

4. Zou Changliang, Yin Guosheng, Feng Long and Wang Zhaojun(2014).Nonparametric maximum likelihood approach to multiple change-point problems. Annals of Statistics.42 (3), 970-1002.

5. Feng Long, Lan Wei, Liu binghui and Ma yanyuan. (2021) Testing for alpha in high-dimensional linear factorpricing models with sparse alternatives. Journal of Econometrics.Accepted.

6. Feng Long and Qiu Peihua (2018) Difference detection between two images for image monitoring.Technometrics, 60, 345-359.

7. Feng Long, Liu binghui and Ma yanyuan. (2021An Inverse Norm Sign Test of Location Parameter for High-Dimensional Data.Journal of Business and Economic Statistics.39 (3), 807-815.

8. Feng Long, Zou Changliang Wang Zhaojun and Zhu Lixing. (2015) Two Sample Behrens-Fisher problem for high-dimensional data. Statistica Sinica. 25, 1297-1312.

9. Feng Long, Wang Zhaojun, Zhang Chunming and Zou Changliang. (2016) Nonparametric testing in regression models with Wilcoxon-type generalized likelihood ratio. Statistica Sinica. 26, 137-155.

10. Feng Long, Zou Changliang Wang Zhaojun and Zhu Lixing (2017) Composite T^2 test for high dimensional data. Statistica Sinica, 27, 1419-1436.

11. Liu binghui,Feng Longand Ma yanyuan. (2021) High-dimensional alpha test of linearfactor pricing models with heavy-tailed distributions. Statistica Sinica. Accepted


其他论文:

1. Feng Long, Zou Changliang, and Wang Zhaojun (2012).local walsh average regression. Journal of Multivariate Analysis. 106(1), 36-48.

2. Feng Long, Zou Changliang, and Wang Zhaojun (2012).Rank-based inference for single-index model Statistics and Probability Letters. 82(3), 535-541.

3. Feng Long, Zou Changliang, Wang Zhaojun and Chen bin (2013). Rank-based score tests for high-dimensional regression coefficients. Electronic Journal of Statistics. 7, 2131-2149.

4. Feng Long, Zou Changliang, Wang Zhaojun, Wei Xianwu and Chen bin. (2015). Robust Spline-Based Variable Selection in Varying Coefficient Model.  Metrika. 78 (1), 85-118.

5. Feng Long, Zou Changliang Wang Zhaojun and Zhu Lixing. (2015) Robust comparison of regression curves. Test. 24 (1), 185-204.

6. Feng Longand Sun Fasheng. (2015). A note on the high dimensional two sample test.Statistics and Probability Letters.105, 29-36.

7. Feng Long and Sun Fasheng. (2016). Spatial sign based high dimensional location test. Electronic Journal of Statistics.10, 2420-2434.

8. Feng Long and Liu binhui (2017). High dimensional rank tests for sphericity. Journal of Multivariate Analysis 155, 217-233.

9. Lan wei, Feng Long and Luo ronghua (2018). Testing high dimensional linear asset pricing model. Journal of Financial Econometrics 16 (2), 191-210.

10. Feng Long, Ren haojieand Zou Changliang (2020). A setwise EWMA scheme for monitoring high-dimensional datastreams.Random Matrices: Theory and Applications. 9, 2050004.

11. Feng Long, Zhang xiaoxu and Liu binghui. (2020) A high-dimensional spatial rank test for two-sample location problems. Computational Statistics and Data Analysis. 144,106889.

12. Feng Long, Zhang xiaoxu and Liu binghui. (2020) Multivariate tests of independence and their application in correlation analysis between financial markets. Journal of Multivariate Analysis.179, 104652.

13. Feng Long, Ding Yanling and Liu Binghui. (2020) Rank-based tests for cross-sectional dependence in large (N,T) fixed effects panel data models. Oxford Bulletin of Economics and Statistics. 82, 1198-1216.

14. Feng Long, Zhao Ping, Ding Yanling, Liu Binghui (2021) Rank-based tests of cross-sectional dependence in large(N; T) panel data models. Computational Statistics and Data Analysis. 153, 107070.

15. Wang hongfei, Feng Long* and Liu Binghui, Zhou Qin.(2021) A class of weighted spatial sign tests for high-dimensional directional data. Electronic Journal of Statistics,15(1),3249-3286.

16. Ding Yanling, Liu Binghui, ZhaoPing  and Feng Long* (2021) Rank-based test for slope homogeneity in highdimensional panel data models. Metrika. Accepted.

17. Feng Long, Zhang xiaoxu and Liu binghui (2021) A high-dimensional spatial rank test for two sample covariance matrices. Statistical Theory and Related Fields. Accepted

18. Zhang Xiaoxu, Zhao Ping and Feng Long*. (2021) Robust sphericity test in the panel data model. Statistics and Probability Letters.Accepted

19. Huang Xifen,  Liu Binghui, and Zhou Qinand Feng Long*. (2022) High-dimensional inverse norm sign test fortwo-sample location problems. Canadian Journal of Statistics.Accepted





学术交流

学术访问经历


2012.3-2012.6        香港浸会大学         朱力行教授

2013.8-2013.9        新加坡国立大学        夏应存教授

2014.2-2014.3        香港大学               尹国圣教授

2021.8-2021.11       南方科技大学         陈欣 副教授


荣誉奖励

2012年 教育部学术新人奖


学术成果