A Kernel Version of Functional Principal Component Analysis

• Autorzy: Tomasz Górecki , Mirosław Krzyśko
• Języki publikacji: EN

Abstrakty

EN

In this paper a new construction of functional principal components (FPCA) is proposed, based on principal components for vector data. A kernel version of FPCA is also presented. The quality of the two described methods was tested on 20 different data sets. (original abstract)

Słowa kluczowe

EN

Functional analysis; Multi-dimensional statistical analysis

PL

Analiza funkcjonalna; Wielowymiarowa analiza statystyczna

• Czasopismo: Statistics in Transition
• Rocznik: 2012
• Tom: 13
• Numer: nr 3
• Strony: 559--568

Twórcy

autor

Tomasz Górecki

• Adam Mickiewicz University in Poznań, Poland

autor

Mirosław Krzyśko

• Adam Mickiewicz University in Poznań, Poland

Bibliografia

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• RAMSAY, J. O., DALZELL, C. J. (1991). Some tools for functional data analysis, J. Royal Statist. Soc. B 53, 539-572.
• RAMSAY, J. O., SILVERMAN, B. W. (2002). Applied Functional Data Analysis, Springer, New York.
• RAMSAY, J. O., SILVERMAN, B. W. (2005). Functional Data Analysis, Springer, New York.
• SEBER, G. A. F. (1984). Multivariate Observations, Wiley, New York.