喻达磊
博士，教授，统计学专业博士生导师
地址：云南省昆明市龙泉路237号，云南财经大学统计与数学学院，统计系。
Email：yudalei AT 126 DOT com
受教育经历：
2001/9-2005/7，学士，云南大学统计系
2005/9-2008/7，硕士，云南大学统计系
2008/9-2011/8，博士，香港城市大学管理科学系
工作经历：

2012/4-2013/7，讲师，云南财经大学

2013/8-2018/9，副教授，云南财经大学

2012/12-2013/12，高级研究助理，香港城市大学

2018/10-至今，教授，云南财经大学
研究兴趣:
随机效应模型、mixture型模型、空间计量经济学模型的统计推断，包括估计理论、模型选择（平均）和稳健估计等。
科研：

论文（Peer reviewed articles）
14. Zhao, S., Liao, J. and Yu, D. (2020). Model averaging estimator in ridge regression and its large sample properties. Statistical Papers, 61, 1719–1739. [SCI]
13. Yu, D., Ding, C., He, N., Wang, R. Zhou, X. and Shi, L. (2019). Robust estimation and confidence interval in meta-regression models. Computational Statistics & Data Analysis, 129, 93–118. [SCI]
12. Yu, D., Zhang, X., and Yau, K.K.W. (2018). Asymptotic properties and information criteria for misspecified generalized linear mixed models.Journal of the Royal Statistical Society: Series B (Statistical Methodology) 80, 817-836. [SCI] (Initial title: “Information criterion for misspecified random effects model”). (MATLAB code and data)
11.Shi, L., Zuo, S.,Yu, D.and Zhou, X. (2017). Influence diagnostics in meta-regression model.Research Synthesis Methods8, 343–354.[SCI]
10. Yu, D.(2016). Conditional Akaike information criteria for a class of Poisson mixture models with random effects.Scandinavian Journal of Statistics431214 –1235. [SCI]
9. Zhang, X.,Yu, D., Zou, G. and Liang, H. (2016). Optimal model averaging estimation for generalized linear models and generalized linear mixed-effects models.Journal of the American Statistical Association 1111775–1790. [SCI]
8. Yu, D., Bai P. and Ding, C. (2015). Adjusted quasi-maximum likelihood estimator for mixed regressive, spatial autoregressive model and its small sample bias.Computational Statistics & Data Analysis87116–135. [SCI] (Initial title: “Restricted quasi-maximum likelihood estimator for mixed regressive, spatial autoregressive model”).
7. Chan, M.-T.,Yu, D., Yau, K.K.W. (2015). Multilevel cumulative logistic regression model with random effects: Application to British social attitudes panel survey data.Computational Statistics & Data Analysis 88173–186. [SCI]
6. Yu, D.and Yau, K.K.W. (2013). Robust REML estimation fork-component Poisson mixture with random effects: application to the epilepsy seizure count data and urinary tract infections data.Statistics in Medicine 322479-2499. [SCI]
5. Yu, D., Zhang, X. and Yau, K.K.W. (2013). Information based model selection criteria for generalized linear mixed models with unknown variance component parameters.Journal of Multivariate Analysis116, 245-262. [SCI]
4. Li, M.,Yu, D.and Bai, P. (2013). A note on the existence and uniqueness of quasi-maximum likelihood estimators for mixed regressive, spatial autoregression models.Statistics and Probability Letters83, 568-572. [SCI]
3. Yu, D.and Yau, K.K.W. (2012). Conditional Akaike information criterion for generalized linear mixed models.Computational Statistics & Data Analysis56, 629-644. [SCI]
2. Yu, D., Yau, K. K. W. and Ding, C., Information based model selection criterion for binary response generalized linear mixed models,The Fifth International Joint Conference on Computational Sciences and Optimization(CSO 2012), 2012.6.24-26, 57-61, Harbin and Wudalianchi, China, 2012, Conference Publications.

1. Ding, C. andYu, D., Statistical inference on progressive type-II censored data from extreme-value distribution,The Fifth International Joint Conference on Computational Sciences and Optimization(CSO 2012), 2012.6.24-26, 62-66, Harbin and Wudalianchi, China, 2012, Conference Publications.




主持的课题


名称 课题编号 来源与类别 经费总额 起止时间
网络邻接矩阵和节点响应变量的共同参数模型：参数估计、模型选择和模型平均 ** 国家自然科学基金项目—面上项目 51万 2021.1-2024.12.
模型误设定时一类广义线性混合模型的模型选择和模型平均研究 ** 国家自然科学基金项目—地区项目 36万 2017.1-2020. 12.
带有随机效应的广义空间自回归模型的统计推断 ** 国家自然科学基金项目—青年项目 23万 2014.1.-2016.12.
多层mixture型泊松回归模型的统计推 断：稳健估计和模型选择 2012FD033 云南省科技计划项目基础研究青年项目 6万 2012.10.-2015.9.
基于条件信息准则的广义线性混合模型之模型选择及统计推断 YC2012D14 云南财经大学引进人才项目 2万 2012.4.-2013.3.
English version

Yu Dalei
Ph.D.Professor of Statistics
Address
Department of Statistics, Statistics and Mathematics College, Yunnan University of Finance and Economics, Kunming, 650221, China
Email：yudalei AT 126 DOT com

Education
·2008 - 2011, Ph.D. in Statistics, Department of Management Sciences, City University of Hong Kong, Hong Kong.
·2005 - 2008, M.S. in Probability Theory and Mathematical Statistics, Department of Statistics, Yunnan University, China.
·2001 - 2005, B.Econ. in Statistics, Department of Statistics, Yunnan University, China.

Academic Experience

·2012/4- 2013/7, Lecturer Yunnan University of Finance and Economics

·2013/8-2018/9, Associate Professor, Yunnan University of Finance and Economics
·2012/12-2013/12, Senior Research Assistant, City University of Hong Kong
·2018/9-present, Professor, Yunnan University of Finance and Economics

Research Interests
Statistical inference in random effects models, finite mixture models, spatial autoregressive models, including estimation theory, model selection and robust estimation.
My main research interest includes random effects models, finite mixture models and spatial autoregressive models.

Publications
Peer reviewed articles

14. Zhao, S., Liao, J. and Yu, D. (2020). Model averaging estimator in ridge regression and its large sample properties. Statistical Papers, 61, 1719–1739. [SCI]
13. Yu, D., Ding, C., He, N., Wang, R. Zhou, X. and Shi, L. (2019). Robust estimation and confidence interval in meta-regression models. Computational Statistics & Data Analysis, 129, 93–118. [SCI]
12. Yu, D., Zhang, X., and Yau, K.K.W. (2018). Asymptotic properties and information criteria for misspecified generalized linear mixed models.Journal of the Royal Statistical Society: Series B (Statistical Methodology) 80, 817-836. [SCI] (Initial title: “Information criterion for misspecified random effects model”). (MATLAB code and data)

11.Shi, L., Zuo, S.,Yu, D.and Zhou, X. (2017). Influence diagnostics in meta-regression model.Research Synthesis Methods8, 343–354.[SCI]
10. Yu, D.(2016). Conditional Akaike information criteria for a class of Poisson mixture models with random effects.Scandinavian Journal of Statistics431214 –1235. [SCI]
9. Zhang, X.,Yu, D., Zou, G. and Liang, H. (2016). Optimal model averaging estimation for generalized linear models and generalized linear mixed-effects models.Journal of the American Statistical Association 1111775–1790. [SCI]
8. Yu, D., Bai P. and Ding, C. (2015). Adjusted quasi-maximum likelihood estimator for mixed regressive, spatial autoregressive model and its small sample bias.Computational Statistics & Data Analysis87116–135. [SCI] (Initial title: “Restricted quasi-maximum likelihood estimator for mixed regressive, spatial autoregressive model”).
7. Chan, M.-T.,Yu, D., Yau, K.K.W. (2015). Multilevel cumulative logistic regression model with random effects: Application to British social attitudes panel survey data.Computational Statistics & Data Analysis 88173–186. [SCI]
6. Yu, D.and Yau, K.K.W. (2013). Robust REML estimation fork-component Poisson mixture with random effects: application to the epilepsy seizure count data and urinary tract infections data.Statistics in Medicine 322479-2499. [SCI]
5. Yu, D., Zhang, X. and Yau, K.K.W. (2013). Information based model selection criteria for generalized linear mixed models with unknown variance component parameters.Journal of Multivariate Analysis116, 245-262. [SCI]
4. Li, M.,Yu, D.and Bai, P. (2013). A note on the existence and uniqueness of quasi-maximum likelihood estimators for mixed regressive, spatial autoregression models.Statistics and Probability Letters83, 568-572. [SCI]
3. Yu, D.and Yau, K.K.W. (2012). Conditional Akaike information criterion for generalized linear mixed models.Computational Statistics & Data Analysis56, 629-644. [SCI]
2. Yu, D., Yau, K. K. W. and Ding, C., Information based model selection criterion for binary response generalized linear mixed models,The Fifth International Joint Conference on Computational Sciences and Optimization(CSO 2012), 2012.6.24-26, 57-61, Harbin and Wudalianchi, China, 2012, Conference Publications.

1. Ding, C. andYu, D., Statistical inference on progressive type-II censored data from extreme-value distribution,The Fifth International Joint Conference on Computational Sciences and Optimization(CSO 2012), 2012.6.24-26, 62-66, Harbin and Wudalianchi, China, 2012, Conference Publications.

Research Grant
l PI: “Shared parameter models for network adjacency matrix and node-specific responses: parameter estimation, model selection and model averaging”, National Natural Science Foundation of China, 2021- 2024; RMB: 510,000.
lPI: “On the model selection and model averaging for a class of generalized linear mixed models with model misspecification”, National Natural Science Foundation of China, 2017- 2020; RMB: 360,000.
lPI: “Statistical inference for generalized spatial autoregressive models with random effects”, Young Scientists Program, National Natural Science Foundation of China, 2014- 2016; RMB: 230,000.
lPI: “Statistical inference for hierarchical mixture Poisson regression: robust estimation and model selection”, Department of Science and Technology of 13 Yunnan Province, 2012-2015: RMB: 60,000.
lPI: “Conditional information criteria for generalized linear mixed model: model selection and statistical inference”, Yunnan University of Finance and Economics, 2012-2013: RMB: 20,000.

matlab code for submission.rar