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 Probabilit s, Universit Paul Sabatier, France |
DOI:
10.1080/02331880600822499
Publication Frequency:
6 issues per year
Subjects:
Mathematical Statistics;
Statistical Theory & Methods;
Statistics;
Statistics for the Biological Sciences;
Stochastic Models & Processes;
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Abstract
The principal components analysis (PCA) in the frequency domain of a stationary p-dimensional time series (Xn)n∈
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.
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| Keywords: Principal components analysis; Time series; Stationarity; Random measure; Spectral analysis; Applications |
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s, Universit
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.
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