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Time-Series Analysis of Variable Star Data


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Matthew Templeton

AAVSO, 25 Birch Street, Cambridge, MA 02138


Based on a workshop session at the 92nd Spring Meeting of the AAVSO, April 25, 2003; revised August 2004


Abstract  Time-series analysis is a rich field of mathematical and statistical analysis, in which physical understanding of a time-varying system can be gained through the analysis of time-series measurements. There are several different techniques of time-series analysis that can be usefully applied to variable star data sets. Some of these techniques are particularly useful for data found in the AAVSO International Database. In this paper, I give a broad overview of time-series analysis techniques useful for variable star data, along with some practical suggestions for the application of different techniques to different types of variables. Included are elementary discussions of traditional Fourier methods, along with wavelet and autocorrelation analysis.

Link to ADS abstract, article and citation information

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