Multiperiodic versus noise variations: mathematical methods

Details Multiperiodic versus noise variations: mathematical methods Multiperiodic versus noise variations: mathematical methods

Mar 2003

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2003aspc..292..391a&link_type=abstract

Interplay of Periodic, Cyclic and Stochastic Variability in Selected Areas of the H-R Diagram. Edited by C. Sterken, ASP Conf. S

Astronomy and Astrophysics

Astronomy

18

Scientific paper

The set of complementary methods for advanced analysis of (irregular) time series are briefly reviewed. This comprises periodogram analysis using harmonic, multi-harmonic and multi-periodic fits with possible prewhitening according to periodic and aperiodic low-frequency trends. For monoperiodic signals with complex shape one may also use non-parametric methods and methods based on characteristic events only. For regularly-spaced data, the autocorrelation function may be restored from the one biased by an arbitrary trend-removal from the finite-length data. The modifications of the scalegram, wavelet and principal component analysis are introduced in more details.

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