张伟平



电 话：+86-
邮 件：zwp@ustc.edu.cn 
所属单位：统计与金融系
个人主页：http://staff.ustc.edu.cn/~zwp/ 

主要研究方向：概率与统计

张伟平，博士，管理学院统计与金融系教授。研究方向为纵向数据分析、贝叶斯统计、统计学习理论、风险度量中的统计方法等。

主持项目：
1.混合多响应纵向数据的均值相关结构同时统计推断方法研究, 国家自然科学基金面上项目, 纵向, 2017-2020
2.纵向数据分析中的有效统计推断方法及其应用, 国家自然科学基金面上项目, 纵向, 2013-2016
3.高通量基因数据分析中的 Bayes 统计方法, 国家青年科学基金项目, 纵向, 2009-2011

参与项目：
1.网络相依结构下金融风险度量及回溯检验研究与应用, 国家自然科学基金面上项目, 参与性质: 参与(排序2/4), 纵向, 2018-2021
2.大数据环境下的评价理论、方法和应用, 国家自然科学基金面上项目, 参与性质: 参与(排序4/10), 纵向, 2017-202
3.极值理论在风险理论中的应用研究, 国家自然科学基金委面上项目, 参与性质: 参与(排序2/3), 纵向, 2012-2015
4.概率论与数理统计, 国家级精品共享资源课程, 参与性质: 参与(排序3/8), 纵向, 2013-2013
5.概率论与数理统计, 国家级精品课程, 参与性质: 参与(排序2/7), 纵向, 2009-2009

主要论著：
[1].Reduced rank modeling for functional regression with functional responses, Journal of Multivariate Analysis, 2019, 169: 205-217
[2].Discrete longitudinal data modeling with a mean-correlation regression approach, Statistica Sinica, 2019, 29: 853-867
[3].THORS: An Efficient Approach for Making Classifiers Cost-Sensitive, IEEE ACCESS, 2019, 7(1): 9770-97718
[4].A New Algorithm for Learning Large Bayesian Network Structure from Discrete Data, IEEE ACCESS, 2019, 7(1): 121665 -121674
[5].Bayesian Joint Semiparametric Mean–Covariance Modeling for Longitudinal Data, Communications in Mathematics and Statistics, 2019, 7(3): 253 -267
[6].Bayesian Nonlinear Quantile Regression Approach for Longitudinal Ordinal Data, Communications in Mathematics and Statistics, 2019, 7(2): 123-140
[7].Second-Order Asymptotics of the Risk Concentration of a Portfolio with Deflated Risks, Mathematical Problems in Engineering, 2018, 2018: 1-12
[8].A joint modeling approach for longitudinal studies, Journal of the Royal Statistical Society Series B-Statistical Methodology, 2015, 77(1): 219-238
[9].A Moving Average Cholesky Factor Model in Covariance Modeling for Longitudinal Data, Biometrika, 2012, 99(1): 141-150
[10].Semiparametric Mean-Covariance Regression Analysis for Longitudinal Data, Journal of the American Statistical Association, 2010, 105(489): 181-193
[11].Smoothing combined estimating equations in quantile regression for longitudinal data, Statistics and Computing, 2014, 24: 123-136
[12].Parsimonious Mean-Covariance modeling for Longitudinal Data with ARMA Errors, Journal of Systems Science and Complexity--English Series, 2019, 32: 1675-1692
[13].A moving average Cholesky factor model in joint mean-covariance modeling for longitudinal data, SCIENCE CHINA Mathematics, 2013, 56(11): 2367-2379
[14].The Superiorities of Bayes Linear Unbiased Estimation in Partitioned Linear model, Journal of Systems Science and Complexity--English Series, 2011, 24(24): 945-954
[15]. 纵向数据中基于偏自相关的均值协方差同时建模, 应用概率统计, 2015, 31(6): 582-595
[16].Precise large deviations for generalized dependent compound renewal risk model with consistent variation, Frontiers of Mathematics in China, 2014, (9): 31-44
[17].The Superiorities of Bayes Linear unbiased Estimator in Multivariate Linear Models, Acta Mathematicae Applicatae Sinica, 2012, 28(2): 383-394
[18].Asymptotic ruin probabilities for proportional investment under interest force with dominatedly-varying-tailed claims, Journal of the Korean Statistical Society, 2012, 41(1): 87-95
[19].A generalized method for the multiple artifacts problem in interlaboratory comparisons with linear trends, Metrologia, 2009, 46(3): 345-350
[20].The superiority of empirical Bayes estimation of parameters in partitioned normal linear model, 数学物理学报（英文版）, 2008, 28(4): 955-962