Tomasz Górecki , Mirosław Krzyśko
ARTICLE

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ABSTRACT

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.

KEYWORDS

PCA, FPCA, kernel version of FPCA.

REFERENCES

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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

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