Asymptotic properties of principal component projections with repeated eigenvalues

Justin Petrovich, Matthew Logan Reimherr

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

In FPCA methods, it is common to assume that the eigenvalues are distinct in order to facilitate theoretical proofs. We relax this assumption, provide a stochastic expansion for the estimated functional principal component projections, and establish their asymptotic normality.

Original languageEnglish (US)
Pages (from-to)42-48
Number of pages7
JournalStatistics and Probability Letters
Volume130
DOIs
StatePublished - Nov 1 2017

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Principal Components
Asymptotic Normality
Asymptotic Properties
Projection
Eigenvalue
Distinct
Principal components
Asymptotic normality
Asymptotic properties
Eigenvalues

All Science Journal Classification (ASJC) codes

  • Statistics and Probability
  • Statistics, Probability and Uncertainty

Cite this

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title = "Asymptotic properties of principal component projections with repeated eigenvalues",
abstract = "In FPCA methods, it is common to assume that the eigenvalues are distinct in order to facilitate theoretical proofs. We relax this assumption, provide a stochastic expansion for the estimated functional principal component projections, and establish their asymptotic normality.",
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Asymptotic properties of principal component projections with repeated eigenvalues. / Petrovich, Justin; Reimherr, Matthew Logan.

In: Statistics and Probability Letters, Vol. 130, 01.11.2017, p. 42-48.

Research output: Contribution to journalArticle

TY - JOUR

T1 - Asymptotic properties of principal component projections with repeated eigenvalues

AU - Petrovich, Justin

AU - Reimherr, Matthew Logan

PY - 2017/11/1

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JO - Statistics and Probability Letters

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