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- W2103265791 abstract "This paper presents a comparison of popular period finding algorithms applied to the light curves of variable stars from the Catalina Real-Time Transient Survey, MACHO and ASAS data sets. We analyse the accuracy of the methods against magnitude, sampling rates, quoted period, quality measures (signal-to-noise and number of observations), variability and object classes. We find that measure of dispersion-based techniques – analysis of variance with harmonics and conditional entropy – consistently give the best results but there are clear dependences on object class and light-curve quality. Period aliasing and identifying a period harmonic also remain significant issues. We consider the performance of the algorithms and show that a new conditional entropy-based algorithm is the most optimal in terms of completeness and speed. We also consider a simple ensemble approach and find that it performs no better than individual algorithms." @default.
- W2103265791 created "2016-06-24" @default.
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- W2103265791 date "2013-08-01" @default.
- W2103265791 modified "2023-09-23" @default.
- W2103265791 title "A comparison of period finding algorithms" @default.
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- W2103265791 doi "https://doi.org/10.1093/mnras/stt1264" @default.
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