A survey of functional principal component analysis

Han Lin Shang*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

111 Citations (Scopus)


Advances in data collection and storage have tremendously increased the presence of functional data, whose graphical representations are curves, images or shapes. As a new area of statistics, functional data analysis extends existing methodologies and theories from the realms of functional analysis, generalized linear model, multivariate data analysis, nonparametric statistics, regression models and many others. From both methodological and practical viewpoints, this paper provides a review of functional principal component analysis, and its use in explanatory analysis, modeling and forecasting, and classification of functional data.
Original languageEnglish
Pages (from-to)121–142
Number of pages22
JournalAStA Advances in Statistical Analysis
Issue number2
Publication statusPublished - Apr 2014
Externally publishedYes


  • Dimension reduction
  • Explanatory analysis
  • Functional data clustering
  • Functional data modeling
  • Functional data forecasting


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