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.
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2022.6.11 |
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Time |
Contents |
Chair |
|
8:20-8:30 |
Opening Ceremony |
Jinhong You |
|
8:30-9:00 |
Invited session，Peter X.K. Song：Multivariate 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 session，Hanlin Shang：Sieve 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 session，Aurore 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 session，Jianhua Huang：Functional 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 session，Shiyuan He：Simultaneous 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 session，Annie Qu：Query-augmented Active Metric Learning (增广查询主动度量学习) |
Ting Li |
|
14:00-14:30 |
Invited session，Lijian Yang：Hypotheses 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 session，Haipeng Shen：Network Regression and Supervised Centrality Estimation
(网络回归和监督中心化估计) |
Xin Liu |
|
15:15-15:45 |
Invited session，Zhenhua Lin：Statistical 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 session，Jane-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 session，Dehan Kong：Causal Inference on Distribution Functions
(分布函数的因果分析) |
Peter
X.K. Song |
|
8:30-9:00 |
Invited session，Peijun Sang：Statistical 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 session，Fang Yao：Intrinsic 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 session，Zhongyi Zhu：Image-on-scalar subgroup regression model (图像标量子组回归模型) |
Jiguo Cao |
|
11:00-11:30 |
Invited session，Liangliang Wang：Online 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 session，Weining Shen：Bayesian 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 session，Haixu Wang：Functional Nonlinear Learning (函数型非线性学习) |
Tao Li |
|
13:40-14:00 |
Student session，Boyui Hu：Simultaneous 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 session，Ying Yang：Online estimation for functional data (函数型数据的在线估计) |
Weiming Li |
|
14:25-14:45 |
Student session，Chao Cheng：Variable 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 |
|
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14:50-15:10 |
Student session，Caihong Qin：Functional 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 session，Zixuan Han：Individual 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 session，Shouxia Wang：Modeling 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) |
|
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15:50-16:00 |
Break and discussion |
|
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16:00-17:00 |
Keynote session，Hans 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 Bai，Shanghai University of Finance and Economics
Tao Huang，Shanghai University of Finance and Economics
Shaoli
Wang，Shanghai University of Finance and Economics
Jinhong You，Shanghai 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.