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A survey of functional principal component analysis

  • Han Lin Shang

    ()

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 fields of functional analysis, generalized linear models, multivariate data analysis, nonparametric statistics and many others. This paper provides a review into functional data analysis with main emphasis on functional principal component analysis, functional principal component regression, and bootstrap in functional principal component regression. Recent trends as well as open problems in the area are discussed.

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File URL: http://business.monash.edu/econometrics-and-business-statistics/research/publications/ebs/wp6-11.pdf
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Paper provided by Monash University, Department of Econometrics and Business Statistics in its series Monash Econometrics and Business Statistics Working Papers with number 6/11.

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Length: 37 pages
Date of creation: May 2011
Date of revision:
Handle: RePEc:msh:ebswps:2011-6
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