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A survey of functional principal component analysis

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  • Han Shang

Abstract

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. Copyright Springer-Verlag Berlin Heidelberg 2014

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  • Han Shang, 2014. "A survey of functional principal component analysis," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 98(2), pages 121-142, April.
    • Handle: RePEc:spr:alstar:v:98:y:2014:i:2:p:121-142
    DOI: 10.1007/s10182-013-0213-1
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