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. (2022) Max-sum tests for cross-sectional independence of high-dimensional panel data. Annals of Statistics. 50(2), 1124-1143.
3. Wang guanghui and Feng Long*. (2023) Computationally efficient and data-adaptive change point inference in high dimensions. Journal of the Royal Statistical Society: Series B 85(3), 936-958.
4. Zou Changliang, Peng Liuhua, Feng Long andWang Zhaojun (2014). Multivariate-signs based high-dimensional tests for sphericity. Biometrika. 101(1), 229-236.
5. 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.
6. Feng Long, Lan Wei, Liu binghui and Ma yanyuan. (2022) High-dimensionaltest for alpha in linear factorpricing models with sparse alternatives. Journal of Econometrics.229(1), 152-175.
7. Wang hongfei, Liu Binghui,Feng Long*and Ma yanyuan. (2023). Rank-based max-sum tests for mutual independence of high-dimensional random vectors. Journal of Econometrics Accepted.
8. Feng Long and Qiu Peihua (2018) Difference detection between two images for image monitoring.Technometrics, 60, 345-359.
9. Feng Long, Liu binghui and Ma yanyuan. (2021) An Inverse Norm Sign Test of Location Parameter for High-Dimensional Data.Journal of Business and Economic Statistics.39 (3), 807-815.
10. Feng Long, Liu binghui and Ma yanyuan. (2023)A one-sided refined symmetrized data aggregation approach to robust mutual fund selection.Journal of Business and Economic Statistics.Accepted
11. Feng Long, Zou Changliang Wang Zhaojun and Zhu Lixing. (2015) Two Sample Behrens-Fisher problem for high-dimensional data. Statistica Sinica. 25, 1297-1312.
12. 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.
13. Feng Long, Zou Changliang Wang Zhaojun and Zhu Lixing (2017) Composite T-2 test for high dimensional data. Statistica Sinica, 27, 1419-1436.
14. Liu binghui,Feng Long*and Ma yanyuan. (2022) High-dimensional alpha test of linearfactor pricing models with heavy-tailed distributions. Statistica Sinica. Online published
15. Feng Long, Jiang Tiefeng,Li Xiaoyun and Liu Binghui. (2023) Asymptotic Independence of the Sum and Maximum of Dependent Random Variables with Applications to High-Dimensional Tests. Statistica Sinica.Accepted
16. Chen dachuan, Song Fengyi and Feng Long*(2023) Rank-based tests for high dimensional white noise. Statistica Sinica.Accepted
其他已发表论文
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 panel data models. Computational Statistics and Data Analysis. 153, 107070.
15. Wang hongfei, Feng Long* and Liu Binghui, Zhou Qin.(2021) An inverse norm weight spatial sign test for high-dimensional directional data. Electronic Journal of Statistics,15(1),3249-3286.
16. Ding Yanling, Liu Binghui, Zhao Ping and Feng Long* (2022) Rank-based test for slope homogeneity in highdimensional panel data models. Metrika. 85(5), 605-626.
17. Feng Long, Zhang xiaoxu and Liu binghui (2022) High-dimensional proportionality test of two covariance matrices and its application to gene expression data.Statistical Theory and Related Fields. 6 (2), 161-174.
18. Zhang Xiaoxu, Zhao Ping and Feng Long*. (2022) Robust sphericity test in the panel data model. Statistics and Probability Letters.182, 109304.
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.Online published.
20. Meng Jing, Feng Long,Zou Changliang,Wang Zhaojun. (2022) Covariate-Assisted Matrix Completion with Multiple Structural Breaks. Journal of Systems Science & Complexity,Accepted.
21. Wang Guanghui, Feng Longand Zhao Ping.(2023) Tests for slope homogeneity in large panel data model. Communications in Mathematics and Statistics.Accepted.
22. Chen dachuan, Feng Long and Liang Decai. (2023). Asymptotic Independence of the Quadratic form and Maximum of Independent Random Variables with Applications to High-Dimensional Tests. Acta Mathematica, English Series,Accepted.
23. Zhang yuhao, Liu yanhong, Feng Long*and Wang Zhaojun. (2023). Testing The Differential Network Between Two Gaussian Graphical Models With False Discovery Rate Control. Journal Of Statistical Computation And SimulationAccepted.
