Resampling techniques for estimating the distribution of descriptive statistics of functional data

Han Lin Shang*

*Corresponding author for this work

Research output: Contribution to journalArticle

4 Citations (Scopus)

Abstract

Resampling methods for estimating the distribution of descriptive statistics of functional data are considered. Through Monte-Carlo simulations, we compare the performance of several resampling methods commonly used for estimating the distribution of descriptive statistics. We introduce two resampling methods that rely on functional principal component analysis, where the scores were randomly drawn from multivariate normal distribution and Stiefel manifold. Illustrated by one-dimensional Canadian weather station data and two-dimensional bone shape data, the resampling methods provide a way of visualizing the distribution of descriptive statistics for functional data.
Original languageEnglish
Pages (from-to)614-635
Number of pages22
JournalCommunications in Statistics - Simulation and Computation
Volume44
Issue number3
DOIs
Publication statusPublished - 2015
Externally publishedYes

Keywords

  • Bootstrap validit
  • Functional mean
  • Functional median
  • Functional variance
  • Smoothed bootstrap
  • Trimmed functional mean
  • Bootstrap validity

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