Functional regression with repeated eigenvalues

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6 Scopus citations

Abstract

We explore the functional principal component method for estimating regression parameters in functional linear models. We demonstrate that the commonly made assumption concerning unique eigenvalues is unnecessary. Convergence rates are established allowing a variety of sample spaces and dependence structures.

Original languageEnglish (US)
Pages (from-to)62-70
Number of pages9
JournalStatistics and Probability Letters
Volume107
DOIs
StatePublished - Dec 1 2015

All Science Journal Classification (ASJC) codes

  • Statistics and Probability
  • Statistics, Probability and Uncertainty

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