杨玥含 教授，硕士生导师、青年龙马学者，统计学学士、博士 Email: yyh@cufe.edu.cn
研究方向 复杂数据建模，因果推断，迁移学习，资产配置
工作经历与教育背景
2023年12月-至今 中央财经大学统计与数学学院，教授
2020年11月-2023年12月 中央财经大学统计与数学学院，副教授
2014年7月-2020年11月 中央财经大学统计与数学学院，讲师
2009年9月-2014年7月 北京大学应用数学专业，获博士学位
2005年9月-2009年7月 重庆大学统计学专业，获学士学位
所授课程
统计软件(本科生)，统计学(本科生)，统计计算(研究生）,论文写作指导（博士）
著作
《金融大数据统计方法与实证》，2016，科学出版社
《金融大数据统计方法与实证配套课件及R程序》，2018，科学出版社
《非负模型选择理论及应用》，2022，中国财政经济出版社
教学、学术奖励
中央财经大学“鸿基世业”优秀学术论文奖
成心优秀实践教学奖
课题
《多重结构数据的多模型/无模型统计分析与因果推断》，国家自然科学基金面上项目，课题负责人，2024.01-2027.12
《大数据驱动的模型分析与最优决策研究》，中央财经大学青年科研创新团队，课题负责人，2023.06 - 2026.06
《高维相关数据分层估计与迭代筛选方法研究及金融实证》，国家自然科学基金青年项目，课题负责人，2021.01-2023.12
《基于“以学为中心”理念的《现代统计软件》教学方法研究和实践》，中央财经大学教学方法研究项目，课题负责人，2022.06-2024.06
《复杂相关数据的筛选建模与金融实证分析》，中央财经大学“青年英才”培育支持计划，课题负责人，2021.06-2023.06
《基于模型选择的有约束统计推断理论及金融大数据分析》，国家自然科学基金面上项目，第一主研，已结项
《罚项约束的模型选择理论及相关问题研究》，中央财经大学青年教师发展基金，课题负责人，已结项
研究生（本科生）科研指导
1.个人状态：对科研有兴趣，在已有的课程中学有余力，计划或确定在本校读研，在本科后半程或即将的研究生阶段开展学术研究。
2.课程基础：熟悉统计学、熟练使用 R or Python or Matlab。
以上，欢迎找我唠嗑。学术是综合的领域，包含文献学习、思考推导、数值分析、英文写作等等，它们需要的不是天赋，而是投入。
科研代表作：Publications on the top journals(*corresponding author)（#student）
1.Hanzhong Liu, Jiyang Ren# and Yuehan Yang*, Randomization-based joint central limit theorem and efficient covariate adjustment in stratified 2^K factorial experiments.Journal of the American Statistical Association,2024,119(545), 136-150. (One ofTop 4Statistical Journals)
2.Hanzhong Liu and Yuehan Yang*, Regression-adjusted average treatment effect estimates instratified randomized experiments, Biometrika, 2020,107(4):935-948.(One ofTop 4Statistical Journals)
3.Ke Zhu#, Hanzhong Liu and Yuehan Yang*, Design-based theory for Lasso adjustment in randomized block experiments and rerandomized experiments, Journal of Businessand Economics Statistics, 2024, in press. (Top Journal in Statistics and Economics)
4.Shun Yu# and Yuehan Yang*, Structured iterative division approach for non-sparse regression models and applications in biological data analysis. Statistical Methods in Medical Research, 2024, 33(7), 1233-1248. (Statistics, Q1).
5.Yuqi Zhang# and Yuehan Yang*, Joint estimation for multisource Gaussian graphical models based on transfer learning. Pattern Recognition, 2025, 158, 110964. (Computer Science, Q1)
6.Zixuan Zhao# and Yuehan Yang*, Nonconvex Fusion Penalties for High-dimensional Hierarchical Categorical Variables. Information Sciences,2024, 680 (2024) 121143.. (Computer Science, Q1)
7.Siwei Xia and Yuehan Yang*, A model-free feature selection technique of feature screening and random forest based recursive feature elimination.International Journal of Intelligent Systems, 2023, 2400194. (Computer Science, Q1)
8.Yuehan Yang*, Dimension reduction of high-dimension categorical data with two or multiple responses regarding the interactions between responses.Expert Systems With Applications, 2023, 221:119753. (Computer Science, Q1)
9.Yimiao Gao# and Yuehan Yang*, Transfer learning on stratified data: joint estimation transferred from strata.Pattern Recognition, 2023, 140:109535.(Computer Science, Q1)
10.SiweiXia and Yuehan Yang*, An iterative model-free feature screening procedure: forward recursive selection by random forest, Knowledge-Based Systems, 2022, 246:108745. (Computer Science, Q1)
11.Xingyu Chen# and Yuehan Yang*, Local linear approximation with Laplacian smoothing penalty and application in biology.Statistical Methods in Medical Research, 2023, 32(6): 1145-1158. (Statistics, Q1)
12.Fan Yang#, Zhanyang Li#, Yushan Xue, and Yuehan Yang*, A penalized least product relative error loss function based on wavelet decomposition for nonparametric multiplicative additive models.Journal of Computational and Applied Mathematics,2023,432:115299. (Mathematics, Q1)
13.Siwei Xia#, Yuehan Yang# and Hu Yang*, High-dimensional Sparse Portfolio Selection with Nonnegative Constraint.Applied Mathematics and Computation, 2023,443:127766. (Mathematics, Q1)
14.Yuehan Yang and Hu Yang*, Adaptive and reversed penalty for analysis ofhigh-dimensional correlated data, Applied Mathematical Modelling, 2021, 92:63-77.(Mathematics, Q1)
15.Yuehan Yang*, Ji Zhu and E. George, MuSP: A Multi-step Screening Procedure for Sparse Recovery,Stat, 2021,10:1-19.(Statistics,Q1,This paper is listed on the Stat Sample Issue as representative of high-dimensional analysis.)
16.Yuehan Yang* and Ji Zhu, A two-step method for estimating high-dimensional Gaussian graphical models. Science China Mathematics, 2020, 63(6):1203-1218. (Mathematics, Top journal)
17.Lan Wu and Yuehan Yang*, Nonnegative Elastic Net and application in index tracking. Applied Mathematics and Computation, 2014, 227:541-552. (Mathematics, Q1)
Published or Accepted (*corresponding author)（#student）
1.Xinyu Dong#, Ziyi Lin, Ziyi Cai and Yuehan Yang*, Adaptive analysis of the heteroscedastic multivariate regression modeling. Journal of Statistical Computation and Simulation, 2024, in press.
2.Yuqi Zhang# and Yuehan Yang*, Joint estimation for multisource Gaussian graphical models based on transfer learning. Pattern Recognition, 2025, 158, 110964.
3.Shun Yu# and Yuehan Yang*, Structured iterative division approach for non-sparse regression models and applications in biological data analysis. Statistical Methods in Medical Research, 2024, 33(7), 1233-1248.
4.Ke Zhu#, Hanzhong Liu and Yuehan Yang*, Blocking, rerandomization, and regression adjustment in randomized experiments with high-dimensional covariates,Journal of Business and Economic Statistics, in press.
5.Weixiong Liang# and Yuehan Yang*, A sequential stepwise screening procedure for sparse recovery in high-dimensional multiresponse models with complex group structures, Statistics and Its Interface, in press.
6.Yaxuan Zhao# and Yuehan Yang*, A robust estimation based on penalized regularization for the varying-coefficient additive model, Journal of Nonparametric Statistics, in press.
7.Zixuan Zhao# and Yuehan Yang*, Nonconvex Fusion Penalties for High-dimensional Hierarchical Categorical Variables. Information Sciences,2024, 680 (2024) 121143.
8.Zhaoyang Li# and Yuehan Yang*, A semi-orthogonal nonnegative matrix tri-factorization algorithm for overlapping community detection, Statistical Papers, 2024, 65:3601–3619.
9.Rui Chen#, Erbo Li#, Yushan Xue, and Yuehan Yang*, Spectral feature selection with the Graphical Lasso estimator for ultra-high dimensional Gaussian graphical models. Statistics and Its Interface, in press.
10.Fan Yang# and Yuehan Yang*, A sparse estimate based on variational approximations for semiparametric generalized additive models, Computational Statistics, 2024, 39:1971-1992.
11.Hanzhong Liu, Jiyang Ren# and Yuehan Yang*, Randomization-based joint central limit theorem and efficient covariate adjustment in stratified 2^K factorial experiments.Journal of the American Statistical Association, 2024,119(545), 136-150.
12.Yuanyuan Cao#, Hongying Li# and Yuehan Yang*, Combining random forest and multicollinearity modeling for index tracking. Communications in Statistics - Simulation and Computation,2024, 53, 3868-3879.
13.ZhaoyangLi# and Yuehan Yang*, Directed association network analysis on the Standard & Poor's 500 Index.Computational Economics,2024, 63:111-127.
14.Yimiao Gao# and Yuehan Yang*, A joint estimation for the high-dimensional regression modeling on stratified data. Communications in Statistics - Simulation and Computation,2023,52(12): 6129-6140.
15.Zhaoyang Li# and Yuehan Yang*, Structurally incoherent adaptive weighted low-rank matrix decomposition for image classification, Applied Intelligence, 2023, 53:25028-25041.
16.Jia Xing#, Binghui Li# and Yuehan Yang*, Community detection and clustering characteristics analysis of the stock market. Managerial and Decision Economics, 2023, 44:3893-3906.
17.Siwei Xia and Yuehan Yang*, A model-free feature selection technique of feature screening and random forest based recursive feature elimination. International Journal of Intelligent Systems, 2023, 2400194.
18.Xingyu Chen# and Yuehan Yang*, Local linear approximation with Laplacian smoothing penalty and application in biology.Statistical Methods in Medical Research, 2023, 32(6): 1145-1158.
19.Yanan Yan# and Yuehan Yang*, Community detection for New York stock market by SCORE-CCD. Computational Statistics, 2023,38:1255-1282.
20.Fan Yang#, Zhanyang Li#, Yushan Xue and Yuehan Yang*, A penalized least product relative error loss function based on wavelet decomposition for nonparametric multiplicative additive models.Journal of Computational and Applied Mathematics,2023,432,115299.
21.Xingyu Chen# and Yuehan Yang*, An iterative algorithm with adaptive weights and sparse Laplacian shrinkage for regression problems. Statistics and Its Interface, 2023,16:433-443.
22.Yimiao Gao# and Yuehan Yang*, Transfer learning on stratified data: joint estimation transferred from strata. Pattern Recognition, 2023, 140:109535.
23.Yuehan Yang*, Dimension reduction of high-dimension categorical data with two or multiple responses regarding the interactions between responses.Expert Systems With Applications, 2023, 221:119753.
24.Siwei Xia#, Yuehan Yang# and Hu Yang*, High-dimensional Sparse Portfolio Selection with Nonnegative Constraint.Applied Mathematics and Computation, 2023,443:127766.
25.Yuehan Yang, Siwei Xia# and Hu Yang*, Multivariate sparse laplacian shrinkage for joint estimation of two graphical network structures, Computational Statistics & Data Analysis, 2023, 178:107620.
26.Yuehan Yang and Siwei Xia#, An integrated precision matrix estimation for multivariate regression problems. Journal of Statistical Planning and Inference, 2023, 222:261-272.
27.Binghui Li# and Yuehan Yang*, Undirected and directed network analysis of the Chinese stock market.Computational Economics, 2022, 60:1155-1173.
28.Siwei Xia# and Yuehan Yang*, An iterative model-free feature screening procedure: forward recursive selection by random forest, Knowledge-Based Systems, 2022, 246:108745.
29.Siwei Xia#,Yuehan Yang and Hu Yang*, Sparse Laplacian shrinkage with the graphical lasso estimator for regression problems, TEST, 2022, 31:255-277.
30.Wenjun Cao#, Lisu Wang# and Yuehan Yang*, Multiple penalized regularization for clusters with varying correlation levels. Statistics and Its Interface, 2022, 15:373-382.
31.Yuehan Yang*, Ji Zhu and E. George, MuSP: A Multi-step Screening Procedure for Sparse Recovery,Stat, 2021,10(1):1-19.
32.Yuehan Yang* and Hu Yang,Rates of Convergence of the Adaptive Elastic Net and the Post-selection Procedure in Ultra-high Dimensional Sparse Models. Communications in Statistics Theory and Methods, 2021,50(1):73-94.
33.Tianchen Gao#, Yan Zhang#, Siyu Wang#,Yuehan Yang and Rui Pan*,Community detection for statistical citation network by D-SCORE, Statistics and Its Interface, 2021,14:279-294.
34.Yuehan Yang and Hu Yang*,Adaptive and reversed penalty for analysis ofhigh-dimensional correlated data, Applied Mathematical Modelling, 2021, 92:63-77.
35.Hanzhong Liu and Yuehan Yang*, Regression-adjusted average treatment effect estimates instratified randomized experiments, Biometrika, 2020,107(4):935-948.
36.Yuehan Yang* and Ji Zhu, A two-step method for estimating high-dimensional Gaussian graphical models. Science China Mathematics, 2020, 63(6):1203-1218.
37.Yuehan Yang* and Lan Wu, A significance test for the elastic net and its asymptotic distribution with general predictors (in Chinese). Science China Mathematics, 2019,49:1119-1138.
38.Yuehan Yang* and Hu Yang, Model selection consistency of lasso for empirical data. Chinese Annals of Mathematics Series B, 2018, 39(4):607-620.
39.Yuehan Yang* and Lan Wu, Nonnegative adaptive lasso for ultra-high dimensional regression models and a two-stage method applied in financial modeling. Journal of Statistical Planning and Inference, 2016, 174:52-67.
40.Lan Wu,Yuehan Yang* and Hanzhong Liu, Nonnegative-lasso and application in index tracking. Computational Statistics and Data Analysis, 2014, 70:116-126.
41.Lan Wu and Yuehan Yang*, Nonnegative Elastic Net and application in index tracking. Applied Mathematics and Computation, 2014,227:541-552.
部分会议邀请报告与境外访问：
2024年12月，访问英国伦敦大学学院
2024年1月，访问澳大利亚国立大学
2024年，澳大利亚 IMS APRM会议，分会主席/邀请报告
2023年，重庆市工业与应用数学学会第九届年会，大会报告
2022年，2023年，海淀医院，邀请报告
2019年，荷兰统计会议
2017年1-2月，访问密歇根大学（期间应邀顺访斯坦福大学）
2018年，2019年，2023年，2024年泛华统计协会国际会议，分会主席/邀请报告
2017年，北大金融数学系20周年系庆系列讲座，北京大学，邀请报告
2015年，2017年，2019年，IMS-China概率统计大会，分会主席/邀请报告
