New perspectives in smoothing: minimax estimation of the mean and principal components of discretized functional data
Angelina Roche – GJM, Volume 7, Issue 2 (2022), 95-107.
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- janvier 12, 2023
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Functional data analysis has been the subject of increasing interest over the past decades. Most existing theoretical contributions assume that the curves are fully observed, whereas in practice the data are observed on a finite grid and may be affected by noise. To account for the presence of noise and discretization, it is common to smooth the data. The purpose of this paper is to review some of the recent literature studying the influence of the observation scheme for estimating the mean and principal components. Some of this work questions the need to smooth the data when the observation grid is fixed.
Milestones:
Received: September 16, 2022
Accepted: October 26, 2022
Published online: January 10, 2023
Authors:
Angelina RocheUniversité Paris-Dauphine, CNRS,
UMR 7534, CEREMADE, 75016 Paris, France.