Estimating activity cycles with probabilistic methods

Author： Olspert N.   Pelt J.   Käpylä M. J.   Lehtinen J.  

Publisher： Edp Sciences

E-ISSN： 1432-0746|615|issue|A111-A111

ISSN： 0004-6361

Source： Astronomy & Astrophysics, Vol.615, Iss.issue, 2018-07, pp. : A111-A111

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Abstract

Context. Period estimation is one of the central topics in astronomical time series analysis, in which data is often unevenly sampled. Studies of stellar magnetic cycles are especially challenging, as the periods expected in those cases are approximately the same length as the datasets themselves. The datasets often contain trends, the origin of which is either a real long-term cycle or an instrumental effect. But these effects cannot be reliably separated, while they can lead to erroneous period determinations if not properly handled.

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