Abstract
Exoplanet research is carried out at the limits of the capabilities of current telescopes and instruments. The studied signals are weak and often embedded in complex systematics from instrumental, telluric, and astrophysical sources. Combining repeated observations of periodic events, simultaneous observations with multiple telescopes, different observation techniques, and existing information from theory and prior research can help to disentangle the systematics from the planetary signals and offers synergistic advantages over analyzing observations separately. Bayesian inference provides a self-consistent statistical framework that addresses both the necessity for complex systematics models and the need to combine prior information and heterogeneous observations. This chapter offers a brief introduction to Bayesian inference in the context of exoplanet research, with focus on time series analysis, and finishes with an overview of a set of freely available programming libraries.
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Parviainen, H. (2018). Bayesian Methods for Exoplanet Science. In: Deeg, H., Belmonte, J. (eds) Handbook of Exoplanets . Springer, Cham. https://doi.org/10.1007/978-3-319-30648-3_149-1
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