张伟平




电 话:+86-551-63600565

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