Abstract
Functional data with non-smooth features (e.g., discontinuities in the functional mean and/or covariance) and monotonicity arise frequently in practice. This paper develops simultaneous inference for concurrent functional linear regression in this setting. We construct a simultaneous confidence band for a functional covariate effect of interest. Along with a Wald-type formulation, our approach is based on a powerful nonparametric likelihood ratio method. Our procedures are flexible enough to allow discontinuities in the coefficient functions and the covariance structure, while accounting for discretization of the observed trajectories under a fixed dense design. A simulation study shows that the proposed likelihood ratio-based procedure outperforms the Wald-type procedure in moderate sample sizes. We apply the proposed methods to studying the effect of age on the occupation time curve derived from wearable device data obtained in an NHANES study. © The Author(s) 2024.
| Original language | English |
|---|---|
| Journal | Sankhya A |
| Online published | 2 Sept 2024 |
| DOIs | |
| Publication status | Online published - 2 Sept 2024 |
Bibliographical note
Full text of this publication does not contain sufficient affiliation information. Research Unit(s) information for this record is based on his previous affiliation.Research Keywords
- 62J99
- Accelerometry
- Bootstrap
- Functional data analysis
- Nonparametric likelihood ratio
- Primary: 62R10
- Secondary: 62G15
Publisher's Copyright Statement
- This full text is made available under CC-BY 4.0. https://creativecommons.org/licenses/by/4.0/
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