基本信息
职称: 教授
系部: 运筹与统计系
办公室: 江南娱乐体育官网入口426-1
办公电话:
Email: guochaohui2010@126.com
社会兼职:
重庆市工业与应用数学学会第五、六届理事会理事;教育部学位中心学位论文通讯评审人、重庆市自然科学基金面上项目通讯评审人、国际数理统计学会(Institute of Mathematical Statistics, IMS)会员。
研究方向:超高维数据分析、变量选择、稳健估计。
主讲课程:
数理统计、应用回归分析、概率论、统计预测与决策、市场调查、统计分析软件(研究生)、实用回归分析(研究生)。
代表论著(*代表通讯作者):
Guo Chaohui(郭朝会) and Li Jialiang*. Homogeneity and Structure Identification in Semiparametric Factor Models. Journal of Business & Economic Statistic(计量经济学顶级期刊),2022,40:1, 408–422 (SCI).
Guo Chaohui(郭朝会), Lv Jing*, Yang Hu, Tu Jingwen and Tian Chenxiao. Semiparametric Model Averaging for Ultrahigh-Dimensional Conditional Quantile Prediction. Acta Mathematica Sinica, English Series, 2023, 39, 1171–1202 (SCI).
Guo Chaohui(郭朝会), Zhang Wenyang*. Model Averaging based Semiparametric Modelling for Conditional Quantile Prediction. SCIENTIA SINICA Mathematica, 2023, accepted, https://doi.org/10.1007/s11425-022-2205-1, (SCI).
Guo Chaohui(郭朝会), Lv Jing* and Wu Jibo. Composite quantile regression for ultra-high dimensional semiparametric model averaging. Computational Statistics & Data Analysis,2021,160:107231 (SCI).
Tu, Jingwen, Yang, Hu, Guo Chaohui*(郭朝会) Lv Jing, 2021. Model averaging marginal regression for high dimensional conditional quantile prediction. Statistical Papers, 62:2661–2689 (SCI).
Lv Jing, Guo Chaohui*(郭朝会),Wu Jibo, 2019. Subject-wise empirical likelihood inference for robust joint mean-covariance model with longitudinal data. Statistics and Its Interface, 12: 617–630. (SCI)
Lv Jing, Guo Chaohui*(郭朝会), Wu Jibo, 2019. Smoothed empirical likelihood inference via the modified Cholesky decomposition for quantile varying coefficient models with longitudinal data. TEST, 28:999–1032. (SCI)
Lv Jing, Guo Chaohui*(郭朝会), 2019. Quantile estimations via modified Cholesky decomposition for longitudinal single-index models. Annals of the institute of statistical mathematics, 71:1163–1199. (SCI)
Lv Jing, Guo Chaohui*(郭朝会), Li Tingting,Hao Yuanyuan, Pan Xiaolin, 2018. Adaptive robust estimation in joint mean–covariance regression model for bivariate longitudinal data [J]. Statistics, 52:64-83. (SCI)
吕晶,郭朝会*,杨虎,李婷婷,2018. 纵向数据的有效秩推断基于修正的Cholesky分解. 数学学报中文版,61: 549-568.
Guo Chaohui*(郭朝会), Yang Hu and Lv Jing. Two step estimations for a single-index varying-coefficient model with longitudinal data. Statistical Papers, 2018, 59:957–983 (SCI).
Lv Jing, Guo Chaohui*(郭朝会), Yang Hu, Li Yalian, 2017. A moving average Cholesky factor model in covariance modeling for composite quantile regression with longitudinal data [J]. Computational Statistics and Data Analysis, 112: 129-144. (SCI)
Lv Jing, Guo Chaohui*(郭朝会), 2017. Efficient parameter estimation via modified Cholesky decomposition for quantile regression with longitudinal data [J]. Computational Statistics, 32: 947-975. (SCI)
Guo Chaohui(郭朝会), Yang Hu, Lv Jing*, 2017. Robust variable selection in high-dimensional varying coefficient models based on weighted composite quantile regression. STATISTICAL PAPERS, 58(4): 1009-1033. (SCI)
Guo Chaohui(郭朝会), Yang Hu, Lv Jing*, 2017. Robust variable selection for generalized linear models with a diverging number of parameters. COMMUNICATIONS IN STATISTICS-THEORY AND METHODS, 46(6): 2967-2981. (SCI)
Guo Chaohui(郭朝会), Yang Hu, Lv Jing*, Wu, Jibo, 2016. Joint estimation for single index mean-covariance models with longitudinal data. JOURNAL OF THE KOREAN STATISTICAL SOCIETY, 45(4): 526-543. (SCI)
Guo Chaohui*(郭朝会), Yang Hu, Lv Jing, 2016. Generalized varying index coefficient models. JOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS, 300(1): 1-17. (SCI)
Yang Hu, Guo Chaohui *(郭朝会), Lv Jing, 2016. Variable selection for generalized varying coefficient models with longitudinal data. STATISTICAL PAPERS, 57:115–132. (SCI)
Yang Hu, Guo Chaohui *(郭朝会), Lv Jing, 2015.SCAD penalized rank regression with a diverging numberof parameters. Journal of Multivariate Analysis, 133: 321–333. (SCI)
Yang Hu, Guo Chaohui *(郭朝会), Lv Jing, 2014. A robust and efficient estimation method for single-index varying-coefficient models. Statistics and Probability Letters, 94 :119–127.(SCI)
主持项目:
国家自然科学基金青年项目,两类半参数因子模型的稳健估计与结构识别(12201091),2023/01-2025/12,30万元,主持;
国家社会科学基金青年项目,面板数据下分位数回归模型的高维变量选择及应用研究(17CTJ015),2017/07-2020/06,20万元,主持;
重庆市基础研究与前沿探索项目,纵向数据下变指标系数模型的统计推断及其应用(cstc2018jcyjA0659),5万元, 2018/07-2021/06,主持;
重庆市自然科学基金面上项目,超高维复杂数据的条件分位数预测(CSTB2022NSCQ-MSX0852),2022/08—2025/07, 主持;
全国统计科学研究项目,超高维面板数据的统计预测及在金融大数据中的应用(2022LY019),2022/07—2024/07,主持;
重庆市教委科学技术研究项目, 大数据背景下的分位数预测(KJQN201900511),2019/10—2022/10,4万元,主持;
重庆市教委科学技术研究项目, 超高维生物大数据的特征筛选与模型平均预测研究(KJQN202100526),2021/10—2024/10,4万元,主持;
国家自然科学基金面上项目,复杂统计数据的参数和半参数模型选择及在金融大数据中的应用(11671059),2017/01-2020/12,48 万元,主研;
重庆市教委科学技术研究项目,纵向单指标模型的稳健变量选择及在金融大数据中的应用(KJ1703054),2017/01—2018/12,3 万元,主持。
荣誉获奖:
2018年入选重庆师范大学(第五批)青年拔尖人才培育计划,10万元, 2019/01—2022/01;2020年度考核优秀;2018-2019年度本科生优秀导师。
重庆师范大学江南娱乐体育官网入口 地址:重庆市沙坪坝区大学城中路37号 汇贤楼电话:023-65362798 邮编:401331