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Bayesian methods are becoming more widely used in asteroseismic analysis. Inparticular, they are being used to determine oscillation frequencies, which arealso commonly found by Fourier analysis. It is important to establish whetherthe Bayesian methods provide an improvement on Fourier methods. We compare,using simulated data, the standard iterative sine-wave fitting method against aMarkov Chain Monte Carlo (MCMC) code that has been introduced to infer purelythe frequencies of oscillation modes (Brewer et al. 2007). A uniform priorprobability distribution function is used for the MCMC method. We find themethods do equally well at determining the correct oscillation frequencies,although the Bayesian method is able to highlight the possibility of amisidentification due to aliasing, which can be useful. In general, we suggestthat the least computationally intensive method is preferable.

A comparison of Bayesian and Fourier methods for frequency determination in asteroseismology