Abstract Number:
1156
Submission Type:
Invited Paper Session
Participants:
Julia Wrobel (1), Julia Wrobel (1), Andrew Leroux (2), Luo Xiao (3), Carmen Tewke (4), Jeffrey Morris (5)
Institutions:
(1) Emory University, Atlanta, GA, (2) University of Colorado, Denver, Colorado, (3) North Carolina State University, Raleigh, NC, (4) Indiana University Bloomington, Bloomington, IN, (5) University of Pennsylvania, Perelman School of Medicine, Philadelphia, PA
Chair:
Session Organizer:
Speaker(s):
Luo Xiao
North Carolina State University
Jeffrey Morris
University of Pennsylvania, Perelman School of Medicine
Session Description:
The last decade has seen a marked increase in development of tools for functional data analysis (fda) to accommodate technical advancement in data storage and continuous data monitoring. These fda methods allow for flexible modeling of associations between high-dimensional data streams and covariates across time or space. In particular, fda methods have been revolutionary for the analysis of wearable device and biomedical imaging data, application areas where previous approaches required data reduction resulting in loss of power and information. In this proposed session, leading statisticians will discuss current methods for functional data analysis motivated by problems arising in biomedical imaging and wearable device data. Our speakers focus on hot topics in fda, including quantile functional regression, computationally efficient methods for ultra-high-dimensional data, and informative information processes.
Specific presentation titles are below.
Andrew Leroux, Assistant Professor: "Fast Generalized Functional Principal Components Analysis for Ultra High Dimensional Data".
Luo Xiao, Professor: "Methods for Functional Data with Informative Observation Process".
Carmen Tewke, Associate Professor: "Semicontinuous Approaches to Correcting for Biases Associated with Zero-Inflated Functional and Scalar Covariates in Sparse Conditional Functional Quantile Regression Models".
Jeff Morris. Professor: "Quantile Functional Regression for Distributional Analysis of Biomedical Imaging Data".
Sponsors:
Caucus for Women in Statistics 2
Section on Statistical Computing 3
WNAR 1
Theme:
Statistics and Data Science: Informing Policy and Countering Misinformation
No
Applied
Yes
Estimated Audience Size
Small (<80)
I have read and understand that JSM participants must abide by the Participant Guidelines.
Yes
I understand and have communicated to my proposed speakers that JSM participants must register and pay the appropriate registration fee by June 1, 2024. The registration fee is nonrefundable.
I understand