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