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On proximity between PCA in the frequency domain and usual PCA 

Authors: Alain Boudou a; Sylvie Viguier-Pla a
Affiliation:   a Laboratoire de Statistique et Probabiliteacutes, Universiteacute Paul Sabatier, France
DOI: 10.1080/02331880600822499
Publication Frequency: 6 issues per year
Published in: journal Statistics, Volume 40, Issue 5 October 2006 , pages 447 - 464
Formats available: HTML (English) : PDF (English)
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Abstract

The principal components analysis (PCA) in the frequency domain of a stationary p-dimensional time series (Xn)nZopf leads to a summarizing time series written as a linear combination series X'n=∑mCm° Xn-m. Therefore, we observe that, when the coefficients Cm, 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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