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On proximity between PCA in the frequency domain and usual PCA
Authors:Alain Boudou  Sylvie Viguier-Pla
Affiliation:1. Laboratoire de Statistique et Probabilités , Université Paul Sabatier , 31062 Toulouse Cedex 4, France boudou@cict.fr;3. Laboratoire de Statistique et Probabilités , Université Paul Sabatier , 31062 Toulouse Cedex 4, France
Abstract:
The principal components analysis (PCA) in the frequency domain of a stationary p-dimensional time series (X n ) n∈? leads to a summarizing time series written as a linear combination series X n =∑ m C m ° X n?m . Therefore, we observe that, when the coefficients C m , m≠0, are close to 0, this PCA is close to the usual PCA, that is the PCA in the temporal domain. When the coefficients tend to 0, the corresponding limit is said to satisfy a property noted 𝒫, of which we will study the consequences. Finally, we will examine, for any series, the proximity between the two PCAs.
Keywords:Principal components analysis  Time series  Stationarity  Random measure  Spectral analysis  Applications
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