Skip to Main content Skip to Navigation
New interface
Preprints, Working Papers, ...

New perspectives in smoothing : minimax estimation of the mean and principal components of discretized functional data.

Abstract : 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 works 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.
Document type :
Preprints, Working Papers, ...
Complete list of metadata

https://hal.archives-ouvertes.fr/hal-03779051
Contributor : Angelina ROCHE Connect in order to contact the contributor
Submitted on : Friday, September 16, 2022 - 1:50:50 PM
Last modification on : Wednesday, October 26, 2022 - 3:54:48 AM

File

SmoothingRochev2.pdf
Files produced by the author(s)

Identifiers

  • HAL Id : hal-03779051, version 1

Collections

Citation

Angelina Roche. New perspectives in smoothing : minimax estimation of the mean and principal components of discretized functional data.. 2022. ⟨hal-03779051⟩

Share

Metrics

Record views

11

Files downloads

19