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2022 International Workshop on Complex Functional Data Analysis


 


The School of Statistics and Management at Shanghai University of Finance and Economics (SUFE) will hold the 2022 International Workshop on Complex Functional Data Analysis virtually on June 11-12, 2022 (Beijing time). The theme of the workshop is “Frontier scientific issues in complex functional data analysis”.

The workshop will discuss the definition, statistical analysis methodology, statistical models and theories of complex functional data. Complex functional data analysis is one of the hotspots of statistics research today, a topic of great importance in both theory and applications. We have invited statisticians from home and abroad, in the areas of complex functional data analysis, to join the workshop. This workshop provides a unique opportunity for statisticians and data scientists to meet online and exchange ideas on the front line of research, recent progress, and future study in complex functional data analysis. The workshop will cover broad areas of topics including complex functional network data analysis, complex functional economic and financial data analysis, complex functional genetic data analysis, statistical theories of complex functional data analysis, and more.

Shanghai University of Finance and Economics (SUFE) is one of the top research institutions in Statistics, Finance and Economics, and Management Sciences in China. There are several research areas in the School of Statistics and Management at SUFE, including Statistics, Machine Learning, Econometrics, Operations Research, and Probability. The School has over 50 faculty members, including 20 tenure-track faculty members and 3 research-track ones. 

 

2022.6.11

Time

Contents

Chair

8:20-8:30

Opening   Ceremony

Jinhong   You

8:30-9:00

Invited   sessionPeter X.K.   SongMultivariate   functional kernel machine regression and sparse functional feature selection   (多元函数型核机器回归和稀疏函数型特征选择)



Liangliang

Wang

9:00-9:30

Invited   sessionHanlin ShangSieve bootstrapping the memory parameter in   long-range dependent stationary functional time series (长期相关平稳函数型时间序列的记忆参数的筛自助法)

9:30-9:45

Break and   discussion

 

9:45-10:45

Keynote   sessionAurore   Delaigle: Estimating a Covariance Function from Fragments of Functional Data   (基于函数型数据片段的协方差函数估计)



Jiguo Cao

10:45-11:00

Break and   discussion

11:00-11:30

Invited   sessionJianhua HuangFunctional data in astronomy: light curves of   Mira variable stars (天文学中的函数型数据:米拉变星的光曲线)



Annie Qu

11:30-12:00

Invited   sessionShiyuan HeSimultaneous inference of periods and   period-luminosity relations for Mira variable stars (米拉变星的周期与周期光度关系的同时推断)

Noon Break

 

13:30-14:00

Invited   sessionAnnie QuQuery-augmented Active Metric Learning (增广查询主动度量学习)



Ting Li

14:00-14:30

Invited   sessionLijian YangHypotheses Testing of Functional Principal   Components  (函数型主成分的假设检验)

14:30-14:45

Break and   discussion

14:45-15:15

Invited   sessionHaipeng ShenNetwork Regression and Supervised Centrality Estimation (网络回归和监督中心化估计)




Xin Liu

15:15-15:45

Invited   sessionZhenhua LinStatistical Inference on Functional Data via   Bootstrapping Max Statistics (基于最大统计量自助法的函数型数据统计推断)

15:45-16:00

Break and   discussion

16:00-17:00

Keynote   sessionJane-Ling   Wang: The trouble with sparsely measured functional data(稀疏测量的函数型数据的困境)

Tao Huang

2022.6.12

 

8:00-8:30

Invited   sessionDehan KongCausal Inference on Distribution Functions (分布函数的因果分析)


Peter X.K. Song

8:30-9:00

Invited   sessionPeijun SangStatistical inference for functional linear   quantile regression (函数型线性分位数回归的统计推断)

9:00-9:15

Break and   discussion

 

9:15-10:15

Keynote   sessionFang YaoIntrinsic Riemannian Functional Data Analysis for   Sparse Longitudinal Observations (稀疏纵向观测的内在黎曼函数型数据分析)

Jinhong   You

10:15-10:30

Break and   discussion

 

10:30-11:00

Invited   sessionZhongyi ZhuImage-on-scalar subgroup regression model (图像标量子组回归模型)




Jiguo Cao

11:00-11:30

Invited   sessionLiangliang   WangOnline   Bayesian learning for mixtures of spatial spline regressions with   mixed-effects (具有混合效应的空间样条回归混合模型的在线贝叶斯学习)

11:30-12:00

Invited   sessionWeining ShenBayesian clustering for spatially correlated   functional data (空间相关函数型数据的贝叶斯聚类)

Noon Break

 

13:20-13:40

Student sessionHaixu WangFunctional Nonlinear Learning (函数型非线性学习)



Tao Li

13:40-14:00

Student sessionBoyui HuSimultaneous Functional Quantile Regression (同时函数型数据分位数回归)

14:00-14:05

Break and discussion

14:05-14:25

Student sessionYing YangOnline estimation for functional data (函数型数据的在线估计)



Weiming Li

14:25-14:45

Student sessionChao ChengVariable selection under logistic regression for   compositional functional data (复合函数型数据的逻辑回归的变量选择)

14:45-14:50

Break and   discussion

14:50-15:10

Student sessionCaihong QinFunctional Two Sample Test based on Projection (基于投影的函数型两样本检验)





Lyuou      Zhang

15:10-15:30

Student sessionZixuan HanIndividual Homogeneity Learning in Distributional   Data Response Additive Models (分布式数据响应可加模型的个体同质性学习)

15:30-15:50

Student sessionShouxia WangModeling for Periodic Functional Time Series in   the Presence of Trend Component (具有趋势性成分的周期性函数型时间序列的建模)

15:50-16:00

Break and discussion

16:00-17:00

Keynote   sessionHans Muller:   Regression Models for Distributional Data (分布式数据的回归模型)

Xingdong     Feng


Organization committee:

 

Chairs

Xingdong Feng, Shanghai University of Finance and Economics

Jiguo Cao, Simon Fraser University


Members

Yang BaiShanghai University of Finance and Economics

Tao HuangShanghai University of Finance and Economics

Shaoli WangShanghai University of Finance and Economics

Jinhong YouShanghai University of Finance and Economics


 

 

Please register for the workshop in advance:

by QRcode


or by website https://www.wjx.top/vj/rXicKCI.aspx

After registration, you will receive a confirmation e-mail containing the zoom link for attending the workshop.