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陈坤(教授)

陈坤
西南财经大学

陈坤,男,西南财经大学统计学院教授、博士生导师。

目录

人物简历

2010年于南京大学数学系获得学士学位,2014年于香港中文大学统计系获得博士学位。2014年加入西南财经大学统计学院。研究方向为时间序列分析、空间统计、函数型数据分析和金融统计。曾多次赴日本早稻田大学、日本北海道大学、台湾中研院、香港中文大学、浙江大学和其他国内外多所高校访问;

教授课程

应用时间序列,金融统计分析,统计学,全英文统计学,文献阅读与论文写作,多元统计分析

Statistical Inference。

学术成果

1. Chan, N.H., Chen, K. and Yau, C.Y. (2014). On the Bartlett correction of empirical likelihood for Gaussian long-memory time series. Electronic Journal of Statistics, 8, 1460-1490;

2. Chen, K., Zhang, L.M. and Pan, M.L. (2014). Spectral methods in spatial statistics. Discrete Dynamics of Nature and Society, Vol. 2014, Article ID 380392.

3. Chen, K., Chan, N.H. and Yau, C.Y. (2016). Bartlett Correction of Empirical Likelihood for Non-Gaussian Short-Memory Time Series. Journal of Time Series Analysis, 37, 624—649.

4. 马丹,刘丽萍,陈坤 (2016). 关联效应还是传染效应。《统计研究》33, 99--106.

5. Chen, K. and Wang, M. (2017). Local Whittle likelihood estimators and tests for spatial lattice data. Journal of Statistical Planning and Inference, 191, 25—42;

6. Chen, K. and Wang, M. (2018). On empirical likelihood for predictability. Communication in Statistics—Theory and Methods, 1--14.

7. Chen, K., Huang, R., Chan, N.H. and Yau, C.Y. (2019). Subgroup analysis of zero-inflated Poisson regression model with applications to insurance data. Insurance: Mathematics and Economics, 86, 8—18.

8. Chen, K., Chan, N.H., Wang, M. and Yau, C.Y. (2019). On Bartlett correction of empirical likelihood for regularly spaced spatial data. Canadian Journal of Statistics, 47, 455--472.

9. Chen, K. Chan, N.H., Yau, C.Y. (2020). Bartlett Correction of frequency domain empirical likelihood for time series with unknown variance. Annals of the Institute of Statistical Mathematics,72,1159--1173.

10. Chan, L.H., Chen, K., Li, C.X., Wong, C.W. and Yau, C.Y. (2020). On higher order moment and cumulant estimation. Journal of Statistical Computation and Simulation,90,747--771.

11. Chen, K. and Huang, R. (2020). Robust empirical likelihood for time series. Journal of Time Series Analysis. (Accepted).

主持项目

1. 国家自然科学基金青年项目,“相依函数型数据的频域似然推断及应用”,项目批准号,项目起止时间2021-2023,主持;

2. 教育部人文社科青年项目,“基于SGLasso正则化算法的研究及其在高维投资组合中的应用”,项目批准号20YJC910001,项目起止时间2020-2022,主持;

3. 国家自然科学基金面上项目,“复杂数据下结构突变模型的统计推断及应用”,项目批准号11871402,项目起止时间2019-2022,参与;

4. 国家自然科学基金青年项目,“两类不完全数据下基于秩及非光滑估计方程的统计推断及应用”,项目批准号1150146,项目起止时间2016-2018,参与;

5. 中央高校基本科研业务项目,“非高斯时间序列数据的经验似然巴特莱特校正研究”,项目起止时间2014-2015,主持。

学术兼职

Referee:

Bernoulli, Statistica Sinica, Journal of Time Series Analysis, Sankhya A, Journal of Forecasting, Journal of the Korean Statistical Society, Empirical Economics, Journal of Testing and Evaluation, International Journal of Mathematics and Statistics, Asia-Pacific Journal of Operation Research.

Member:

Institute of Mathematical Statistics; American Statistician Association;

参加会议

2019 Invited talk, “Subgroup analysis of zero-inflated Poisson regression model with applications to insurance data”. ICSA China, Zhejiang University, Hangzhou.

2019 Invited talk, "On model selection of ARFIMA and GARCH Processes". Institute of Statistics and Big Data, Beijing.

2019 Invited talk, “Bartlett correction for empirical likelihood for spatial lattice data”. ICSA China, Nankai University, Tianjing.

2018 Invited talk, “Subgroup analysis of zero-inflated Poisson regression model with applications to insurance data”. School of Management, Donghua University, Shanghai.

2017 Invited talk, “Bartlett correction of empirical likelihood for time series”, 1st International Conference on Econometrics and Statistics. Hong Kong University of Science and Technology, Hong Kong.

2015 Invited talk, “On Bartlett correction of empirical likelihood in Gaussian long-memory time series”, Department of Finance, Nanjing University.

2013 Presenter, “On Bartlett correction of empirical likelihood in Gaussian long-memory time series”, Young Statistician’s Meeting, Hong Kong.

2013 Presenter, “On Bartlett correction of empirical likelihood in non-Gaussian short-memory time series”, The Second International Conference on Engineering and Computational Mathematics, Hong Kong.[1]

参考资料