´¡³Ü³Ù³ó´Ç°ù:ÌýGeraint J. A. Harker
´¡²ú²õ³Ù°ù²¹³¦³Ù:ÌýThe precise form of the foregrounds for sky-averaged measurements of the 21-cm line during and before the epoch of reionization is unknown. We suggest that the level of complexity in the foreground models used to fit global 21-cm data should be driven by the data, under a Bayesian model selection methodology. A first test of this approach is carried out by applying nested sampling to simplified models of global 21-cm data to compute the Bayesian evidence for the models. If the foregrounds are assumed to be polynomials of order n in log–log space, we can infer the necessity to use n = 4 rather than n = 3 with <2 h of integration with limited frequency coverage, for reasonable values of the n = 4 coefficient. Using a higher order polynomial does not necessarily prevent a significant detection of the 21-cm signal. Even for n = 8, we can obtain very strong evidence distinguishing a reasonable model for the signal from a null model with 128 h of integration. More subtle features of the signal may, however, be lost if the foregrounds are this complex. This is demonstrated using a simpler model for the signal that only includes absorption. The results highlight some pitfalls in trying to quantify the significance of a detection from errors on the parameters of the signal alone.