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Studies in astronomical time series analysis. III - Fourier transforms, autocorrelation functions, and cross-correlation functions of unevenly spaced dataThis paper develops techniques to evaluate the discrete Fourier transform (DFT), the autocorrelation function (ACF), and the cross-correlation function (CCF) of time series which are not evenly sampled. The series may consist of quantized point data (e.g., yes/no processes such as photon arrival). The DFT, which can be inverted to recover the original data and the sampling, is used to compute correlation functions by means of a procedure which is effectively, but not explicitly, an interpolation. The CCF can be computed for two time series not even sampled at the same set of times. Techniques for removing the distortion of the correlation functions caused by the sampling, determining the value of a constant component to the data, and treating unequally weighted data are also discussed. FORTRAN code for the Fourier transform algorithm and numerical examples of the techniques are given.
Document ID
19890062857
Acquisition Source
Legacy CDMS
Document Type
Reprint (Version printed in journal)
External Source(s)
Authors
Scargle, Jeffrey D.
(NASA Ames Research Center Moffett Field, CA, United States)
Date Acquired
August 14, 2013
Publication Date
August 15, 1989
Publication Information
Publication: Astrophysical Journal, Part 1
Volume: 343
ISSN: 0004-637X
Subject Category
Astronomy
Accession Number
89A50228
Distribution Limits
Public
Copyright
Other

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