Curve registration

J. O. Ramsay, Xiaochun Li

Research output: Contribution to journalArticlepeer-review

228 Scopus citations

Abstract

Summary. Functional data analysis involves the extension of familiar statistical procedures such as principal components analysis, linear modelling and canonical correlation analysis to data where the raw observation xi is a function. An essential preliminary to a functional data analysis is often the registration or alignment of salient curve features by suitable monotone transformations hi, of the argument t, so that the actual analyses are carried out on the values x,{/7,(f)}- This is referred to as dynamic time warping in the engineering literature. In effect, this conceptualizes variation among functions as being composed of two aspects: horizontal and vertical, or domain and range. A nonparametric function estimation technique is described for identifying the smooth monotone transformations ht and is illustrated by data analyses. A second-order linear stochastic differential equation is proposed to model these components of variation.

Original languageEnglish (US)
Pages (from-to)351-363
Number of pages13
JournalJournal of the Royal Statistical Society. Series B: Statistical Methodology
Volume60
Issue number2
DOIs
StatePublished - Jan 1 1998
Externally publishedYes

Keywords

  • Dynamic time warping
  • Geometric brownian motion
  • Monotone functions
  • Spline
  • Stochastic time
  • Time warping

ASJC Scopus subject areas

  • Statistics and Probability
  • Statistics, Probability and Uncertainty

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