The 4 demographic scenarios (Models A–D) and their associated Bayes factors. Model A is the model with constant population size, *N*_{0}. Model B is a model with an exponentially growing population size (present size, *N*_{0}, ancestral size, *N*_{1}, time since the onset of expansion, *t*_{0}). In Model C, the growth is exponential between two periods with constant size (present size, *N*_{0}, ancestral size, *N*_{1}, time since the onset of expansion, *t*_{0}, time since the end of expansion, *t*_{1}). Model D is similar to Model B, but it includes an ancient bottleneck before expansion. Variants of these 4 models, including variable mutation rates across loci, are considered here. The Bayes factors (top boxes) correspond to the ratio of the weight of evidence of each model to the weight of evidence of Model B. Two window sizes, *δ*_{0.01} and *δ*_{0.05}, were used when computing the Bayes factors. These window sizes correspond to the 1% and 5% quantiles of the distance between the values of the summary statistics obtained under Model B and the observed values of the summary statistics. The Bayes factors were identical for the 2 window sizes and for values rounded for one decimal place, except for Model C, for which a minor difference was observed (1.8 for *δ*_{0.05} instead of 1.9).

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