Problemy decyzyjne w funkcjonal-nej analizie głównych składowych
Decision problems in functional principal components analysis

Summary/Abstract: The functional principal components analysis combines advantages of the standard principal components analysis and enables analyzing data with dynamic nature. The main difference in both methods is the type of data: the PCA is based on multivariate data, whereas the FPCA on the functional data including curves and trajectories, i.e. a series of individual observations, not a single observation, as usual. The purpose of this article is to characterize the functional stages of principal component analysis with a special discussion of the steps that are not present in the classical principal component analysis.

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