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Activity Number: 471 - New Frontier in Developments of Complex-Structured High-Dimensional Data Analysis
Type: Topic Contributed
Date/Time: Wednesday, August 10, 2022 : 2:00 PM to 3:50 PM
Sponsor: International Chinese Statistical Association
Abstract #320824
Title: Functional Group Lasso with Functional Predictor Selection
Author(s): Jun Song* and Ali Mahzarnia
Companies: Korea University and UNC Charlotte
Keywords: functional group lasso; sparse estimation; covariate selection

In this talk, we will discuss functional predictor selection along with the estimation of smooth functional coefficients in a simultaneous fashion in a scalar-on-function regression problem under a high-dimensional multivariate functional data setting. In particular, we develop a method for functional group-sparse regression under a generic Hilbert space of infinite dimension. Each group is based on an infinite-dimensional space. Then we show the convergence of algorithms and the consistency of the estimation and selection under infinite-dimensional Hilbert spaces. Simulation and fMRI data application will be presented at the end to show the effectiveness of the methods in both the selection and estimation of functional coefficients.

Authors who are presenting talks have a * after their name.

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