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Table 2 The models evaluated in the simulation-based analyses

From: An improved approximate-Bayesian model-choice method for estimating shared evolutionary history

  Priors
Model t τ θ  
M m s B a y e s tD U{1,…,Y} τU(0,10 [ 25 M G A]) θ A U(0,0.05) θ ̄ D U(0,0.05)
M U s h a p e d tD U{1,…,Y} τE x p(m e a n=2.887[ 7.22M G A]) θ A θD1θD2E x p(m e a n=0.025)
M U n i f o r m tD U{a(Y)} τE x p(m e a n=2.887[ 7.22M G A]) θ A θD1θD2E x p(m e a n=0.025)
M D P P tD P(χG a m m a(·,·)) τE x p(m e a n=2.887[ 7.22M G A]) θ A θD1θD2E x p(m e a n=0.025)
  1. For the M D P P model, the prior on the concentration parameter, χ Gamma (·,·), was set to Gamma(2,2) for the validation analyses and Gamma(1.5,18.1) for the power analyses. The distributions of divergence times are given in units of 4N C generations followed in brackets by units of millions of generations ago (MGA), with the former converted to the latter assuming a per-site rate of 1×10−8 mutations per generation. For model M m s B a y e s , the priors for theta parameters are θ A U(0, 0.05) and θD1,θD2 Beta(1, 1)×2× U(0, 0.05). The later is summarized as θ ̄ D U(0, 0.05). For the M D P P and M U n i f o r m , and M U s h a p e d models, θ A ,θD1, and θD2 are independently and exponentially distributed with a mean of 0.025.