360博彩通-大发888卡-老虎机作弊器手机软件

簡(jiǎn)介

上海對(duì)外經(jīng)貿(mào)大學(xué)統(tǒng)計(jì)與數(shù)據(jù)科學(xué)學(xué)院副院長(zhǎng)，教授，碩士生導(dǎo)師。擔(dān)任中國(guó)現(xiàn)場(chǎng)統(tǒng)計(jì)研究會(huì)大數(shù)據(jù)統(tǒng)計(jì)分會(huì)常務(wù)理事和統(tǒng)計(jì)交叉科學(xué)研究分會(huì)理事。2003-2015年在太原師范學(xué)院工作，2016年入職上海對(duì)外經(jīng)貿(mào)大學(xué)。2019-2020年到新加坡國(guó)立大學(xué)進(jìn)行學(xué)術(shù)訪(fǎng)問(wèn)。主要從事統(tǒng)計(jì)學(xué)的理論、方法和應(yīng)用研究，主持國(guó)家社會(huì)科學(xué)基金一般項(xiàng)目、教育部人文社會(huì)科學(xué)研究規(guī)劃基金項(xiàng)目、全國(guó)統(tǒng)計(jì)科學(xué)研究重點(diǎn)項(xiàng)目、教育部重點(diǎn)實(shí)驗(yàn)室項(xiàng)目和上海市科學(xué)技術(shù)委員會(huì)項(xiàng)目等，在統(tǒng)計(jì)學(xué)SCI權(quán)威期刊JBES、Statistica Sinica、SJS、JMA、JSPI等發(fā)表學(xué)術(shù)論文30余篇。

部分發(fā)表論文

1. Liu, J., Li, R., & Lian, H. (2024). Distributed estimation of functional linear regression with functional responses. Metrika, 87(1), 21-30. 

2. Yang, Y., Wang, L., Liu, J., Li, R., & Lian, H. (2023). Communication-efficient estimation of quantile matrix regression for massive datasets. Computational Statistics & Data Analysis, 187, 107812.

3. Zhao, W., Zhang, X., Yuen, K. C., Li, R., & Lian, H. (2023). Estimation in quantile regression models for correlated data with diverging number of covariates and large cluster sizes. Communications in Statistics-Theory and Methods, 52(4), 1012-1038.

4. Li R., Leng C. L. and You J. H. (2022). Semiparametric tail index regression. Journal of Business & Economic Statistics. 40(1): 82-95. 

5. Wang, Y., Zhou, Y., Li, R., and Lian, H. (2022). Sparse high-dimensional semi-nonparametric quantile regression in a reproducing kernel Hilbert space. Computational Statistics & Data Analysis, 168, 107388. 

6. Li, R., Lu, W., Zhu, Z. and Lian, H. (2021). Optimal prediction of quantile functional linear regression in reproducing kernel Hilbert spaces. Journal of Statistical Planning and Inference, 211, 162-170.

7. Zhang F., Li R. and Lian H. (2021). Approximate nonparametric quantile regression in reproducing kernel Hilbert spaces via random projection. Information Sciences. 547(8): 244-254. 

8. Li, R. and Zhang, Y. (2021). Two-stage estimation and simultaneous confidence band in partially nonlinear additive model. Metrika, 84(8), 1109-1140.

9. Li, R., Mu, S., & Hao, R. (2021). Estimation and variable selection for partially linear additive models with measurement errors. Communications in Statistics-Theory and Methods, 50(6), 1416-1445.

10. Zhu, H., Li, R., Zhang, R. and Lian, H. (2020). Nonlinear functional canonical correlation analysis via distance covariance. Journal of Multivariate Analysis, 180, 104662. 

11. Zhang, F., Wang, X., Li, R. and Lian, H. (2020). Randomized sketches for sparse additive models. Neurocomputing, 385, 80-87.

12. Zhao, W., Zhang, F., Li, R. and Lian, H. (2020). Principal single-index varying-coefficient models for dimension reduction in quantile regression. Journal of Statistical Computation and Simulation, 90(5), 800-818.

13. Xu, Q. F. and Li, R. (2019). A double varying-coefficient modeling approach for analyzing longitudinal observations. Acta Mathematicae Applicatae Sinica, English Series, 35(3), 671-688. 

14. Xiong, X., Li, R. and Lian, H. (2019). On nonparametric randomized sketches for kernels with further smoothness. Statistics & Probability Letters, 153, 139-142.

15. Li R. and Zhao H. B. (2018). Sparsity identification for high-dimensional partially linear model with measurement error, Communications in Statistics-Simulation and Computation, 47(8), 2378-2392. 

16. Li R., Leng C. L. and You J. H., (2017). A semiparametric regression model for longitudinal data with non-stationary errors, Scandinavian Journal of Statistics, 44(4), 932-950. 

17. Li R. and Hao R. L. (2017). Effective identification and estimation for the semiparametric measurement error model, Journal of the Korean Statistical Society, 46(1), 1-14.

18. Li R., Alan T.K. Wan and You J.H. (2016). Semiparametric GMM estimation and variable selection in dynamic panel data models with fixed effects，Computational Statistics and Data Analysis, 100, 401-423.

19. Li R., Li X. and Zhou X. (2016). Efficient inference for longitudinal data varying-coefficient regression models，Australian & New Zealand Journal of Statistics, 57(4) , 545-570.

20. Zhao H.B. and Li R. (2016). Difference based estimation and model identification for panel data semiparametric models with cross-section dependence, Communications in Statistics-Theory and Methods, 45(4), 1099-1117. 

21. Bai Y., Huang J., Li R. and You J. H. (2015). Semiparametric longitudinal model with irregular time autoregressive error process, Statistica Sinica, 25(2), 507-528.

22. Li R. and Zhou X. (2015). Efficient estimation and variable selection in dynamic panel data partially linear varying coefficient models with incidental parameter, Acta Mathematicae Alicatae Sinica, English Series, 31(3), 643-664.

科研項(xiàng)目

1. 教育部人文社會(huì)科學(xué)研究規(guī)劃基金項(xiàng)目《大規(guī)模面板數(shù)據(jù)交互效應(yīng)動(dòng)態(tài)指標(biāo)模型的結(jié)構(gòu)識(shí)別與穩(wěn)健估計(jì)》, 2023/10-2024/09, 主持

2. 統(tǒng)計(jì)與數(shù)據(jù)科學(xué)前沿理論及應(yīng)用教育部重點(diǎn)實(shí)驗(yàn)室項(xiàng)目《商務(wù)大數(shù)據(jù)建模分析：理論、算法與應(yīng)用研究》，2019/01-2020/12，主持

3. 國(guó)家社會(huì)科學(xué)基金一般項(xiàng)目《非線(xiàn)性動(dòng)態(tài)面板數(shù)據(jù)模型的統(tǒng)計(jì)推斷與應(yīng)用研究》，2017/09-2022/08，主持

4. 全國(guó)統(tǒng)計(jì)科學(xué)研究重點(diǎn)項(xiàng)目《基于大數(shù)據(jù)背景的半?yún)?shù)建模方法及其應(yīng)用研究》，2017/01-2018/12，主持

5. 上海市高校青年教師培養(yǎng)資助計(jì)劃《關(guān)于幾類(lèi)復(fù)雜數(shù)據(jù)的結(jié)構(gòu)化建模與統(tǒng)計(jì)推斷》，2017/01至2018/12，主持

6. 上海市科學(xué)技術(shù)委員會(huì)項(xiàng)目《高維復(fù)雜數(shù)據(jù)的稀疏化建模及應(yīng)用研究》，2016/09-2018/08，主持

7. 國(guó)家自然科學(xué)基金面上項(xiàng)目《遷移學(xué)習(xí)和聯(lián)邦學(xué)習(xí)研究及在民航大數(shù)據(jù)的應(yīng)用》，2024/01-2027/12，參與

8. 國(guó)家自然科學(xué)基金天元項(xiàng)目《基于傳染模型的信用衍生品定價(jià)研究》，2014/1-2014/12，參與