Model selection with abc - cross validation - based on 100 samples
Confusion matrix based on 100 samples for each model.

$tol0.005
        Dayhoff Neutral Fitness
Dayhoff      96       1       3
Neutral       0     100       0
Fitness       3       0      97


Mean model posterior probabilities (neuralnet)

$tol0.005
        Dayhoff Neutral Fitness
Dayhoff  0.9346  0.0051  0.0603
Neutral  0.0002  0.9676  0.0322
Fitness  0.0318  0.0229  0.9452




Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (1500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.9973  0.0027 

Bayes factors:
         Dayhoff  Neutral  Fitness
Dayhoff            0.0000   0.0000
Neutral      Inf   1.0000 374.0000
Fitness      Inf   0.0027   1.0000





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (1500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
  0.000   0.786   0.214 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  3.6729
Fitness     Inf  0.2723  1.0000





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (1500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.9727  0.0273 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000 35.5854
Fitness     Inf  0.0281  1.0000





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (1500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.9987  0.0013 

Bayes factors:
         Dayhoff  Neutral  Fitness
Dayhoff            0.0000   0.0000
Neutral      Inf   1.0000 749.0000
Fitness      Inf   0.0013   1.0000





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (1500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
  0.000   0.964   0.036 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000 26.7778
Fitness     Inf  0.0373  1.0000





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (1500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0713  0.6853  0.2433 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.1041  0.2932
Neutral  9.6075  1.0000  2.8164
Fitness  3.4112  0.3551  1.0000


Posterior model probabilities (neuralnet):
Dayhoff Neutral Fitness 
 0.0000  0.9999  0.0001 

Bayes factors:
            Dayhoff     Neutral     Fitness
Dayhoff      1.0000      0.0000      0.0091
Neutral 920956.2111      1.0000   8338.2741
Fitness    110.4493      0.0001      1.0000




Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (1500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
  0.000   0.996   0.004 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff           0.000   0.000
Neutral     Inf   1.000 249.000
Fitness     Inf   0.004   1.000





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (1500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
  0.000   0.996   0.004 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff           0.000   0.000
Neutral     Inf   1.000 249.000
Fitness     Inf   0.004   1.000





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (1500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0247  0.6147  0.3607 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.0401  0.0684
Neutral 24.9189  1.0000  1.7043
Fitness 14.6216  0.5868  1.0000


Posterior model probabilities (neuralnet):
Dayhoff Neutral Fitness 
 0.0006  0.9948  0.0047 

Bayes factors:
          Dayhoff   Neutral   Fitness
Dayhoff    1.0000    0.0006    0.1190
Neutral 1785.2301    1.0000  212.5053
Fitness    8.4009    0.0047    1.0000




Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (1500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
  0.000   0.972   0.028 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000 34.7143
Fitness     Inf  0.0288  1.0000





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (1500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0513  0.6380  0.3107 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.0805  0.1652
Neutral 12.4286  1.0000  2.0536
Fitness  6.0519  0.4869  1.0000


Posterior model probabilities (neuralnet):
Dayhoff Neutral Fitness 
 0.0000  0.9999  0.0001 

Bayes factors:
             Dayhoff      Neutral      Fitness
Dayhoff       1.0000       0.0000       0.0090
Neutral 1838361.6624       1.0000   16495.7503
Fitness     111.4446       0.0001       1.0000




Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (1500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.9653  0.0347 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000 27.8462
Fitness     Inf  0.0359  1.0000





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (1500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
      0       1       0 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff               0        
Neutral     Inf       1     Inf
Fitness               0        





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (1500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
  0.000   0.992   0.008 

Bayes factors:
         Dayhoff  Neutral  Fitness
Dayhoff            0.0000   0.0000
Neutral      Inf   1.0000 124.0000
Fitness      Inf   0.0081   1.0000





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (1500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.9993  0.0007 

Bayes factors:
          Dayhoff   Neutral   Fitness
Dayhoff              0.0000    0.0000
Neutral       Inf    1.0000 1499.0000
Fitness       Inf    0.0007    1.0000





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (1500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
      0       1       0 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff               0        
Neutral     Inf       1     Inf
Fitness               0        





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (1500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.9993  0.0007 

Bayes factors:
          Dayhoff   Neutral   Fitness
Dayhoff              0.0000    0.0000
Neutral       Inf    1.0000 1499.0000
Fitness       Inf    0.0007    1.0000





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (1500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
      0       1       0 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff               0        
Neutral     Inf       1     Inf
Fitness               0        





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (1500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.9987  0.0013 

Bayes factors:
         Dayhoff  Neutral  Fitness
Dayhoff            0.0000   0.0000
Neutral      Inf   1.0000 749.0000
Fitness      Inf   0.0013   1.0000





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (1500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.9813  0.0187 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000 52.5714
Fitness     Inf  0.0190  1.0000





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (1500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
      0       1       0 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff               0        
Neutral     Inf       1     Inf
Fitness               0        





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (1500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
      0       1       0 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff               0        
Neutral     Inf       1     Inf
Fitness               0        





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (1500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.2367  0.4320  0.3313 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.5478  0.7143
Neutral  1.8254  1.0000  1.3038
Fitness  1.4000  0.7670  1.0000


Posterior model probabilities (neuralnet):
Dayhoff Neutral Fitness 
 0.0024  0.9825  0.0152 

Bayes factors:
         Dayhoff  Neutral  Fitness
Dayhoff   1.0000   0.0024   0.1578
Neutral 410.7523   1.0000  64.8276
Fitness   6.3361   0.0154   1.0000




Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (1500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0013  0.8567  0.1420 

Bayes factors:
         Dayhoff  Neutral  Fitness
Dayhoff   1.0000   0.0016   0.0094
Neutral 642.5000   1.0000   6.0329
Fitness 106.5000   0.1658   1.0000


Posterior model probabilities (neuralnet):
Dayhoff Neutral Fitness 
 0.0001  0.9921  0.0078 

Bayes factors:
          Dayhoff   Neutral   Fitness
Dayhoff    1.0000    0.0001    0.0168
Neutral 7562.2327    1.0000  127.4115
Fitness   59.3528    0.0078    1.0000




Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (1500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.9987  0.0013 

Bayes factors:
         Dayhoff  Neutral  Fitness
Dayhoff            0.0000   0.0000
Neutral      Inf   1.0000 749.0000
Fitness      Inf   0.0013   1.0000





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (1500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.9987  0.0013 

Bayes factors:
         Dayhoff  Neutral  Fitness
Dayhoff            0.0000   0.0000
Neutral      Inf   1.0000 749.0000
Fitness      Inf   0.0013   1.0000





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (1500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0193  0.7060  0.2747 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.0274  0.0704
Neutral 36.5172  1.0000  2.5704
Fitness 14.2069  0.3890  1.0000


Posterior model probabilities (neuralnet):
Dayhoff Neutral Fitness 
 0.0000  0.9999  0.0001 

Bayes factors:
             Dayhoff      Neutral      Fitness
Dayhoff       1.0000       0.0000       0.0113
Neutral 1086188.4558       1.0000   12312.4727
Fitness      88.2185       0.0001       1.0000




Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (1500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.7453  0.2547 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  2.9267
Fitness     Inf  0.3417  1.0000





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (1500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
      0       1       0 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff               0        
Neutral     Inf       1     Inf
Fitness               0        





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (1500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.9253  0.0747 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000 12.3929
Fitness     Inf  0.0807  1.0000





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (1500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.9987  0.0013 

Bayes factors:
         Dayhoff  Neutral  Fitness
Dayhoff            0.0000   0.0000
Neutral      Inf   1.0000 749.0000
Fitness      Inf   0.0013   1.0000





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (1500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.9667  0.0333 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000 29.0000
Fitness     Inf  0.0345  1.0000





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (1500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0847  0.6007  0.3147 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.1410  0.2691
Neutral  7.0945  1.0000  1.9089
Fitness  3.7165  0.5239  1.0000


Posterior model probabilities (neuralnet):
Dayhoff Neutral Fitness 
 0.0053  0.9671  0.0276 

Bayes factors:
         Dayhoff  Neutral  Fitness
Dayhoff   1.0000   0.0055   0.1911
Neutral 183.0870   1.0000  34.9790
Fitness   5.2342   0.0286   1.0000




Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (1500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.9947  0.0053 

Bayes factors:
         Dayhoff  Neutral  Fitness
Dayhoff            0.0000   0.0000
Neutral      Inf   1.0000 186.5000
Fitness      Inf   0.0054   1.0000





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (1500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.9893  0.0107 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000 92.7500
Fitness     Inf  0.0108  1.0000





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (1500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
      0       1       0 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff               0        
Neutral     Inf       1     Inf
Fitness               0        





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (1500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
      0       1       0 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff               0        
Neutral     Inf       1     Inf
Fitness               0        





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (1500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
  0.000   0.942   0.058 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000 16.2414
Fitness     Inf  0.0616  1.0000





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (1500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.2087  0.5033  0.2880 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.4146  0.7245
Neutral  2.4121  1.0000  1.7477
Fitness  1.3802  0.5722  1.0000


Posterior model probabilities (neuralnet):
Dayhoff Neutral Fitness 
 0.0002  0.9991  0.0007 

Bayes factors:
          Dayhoff   Neutral   Fitness
Dayhoff    1.0000    0.0002    0.2293
Neutral 5827.0522    1.0000 1336.0758
Fitness    4.3613    0.0007    1.0000




Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (1500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.1893  0.4540  0.3567 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.4170  0.5308
Neutral  2.3979  1.0000  1.2729
Fitness  1.8838  0.7856  1.0000


Posterior model probabilities (neuralnet):
Dayhoff Neutral Fitness 
 0.0610  0.4808  0.4582 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.1270  0.1332
Neutral  7.8761  1.0000  1.0494
Fitness  7.5056  0.9530  1.0000




Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (1500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.9133  0.0867 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000 10.5385
Fitness     Inf  0.0949  1.0000





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (1500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
  0.000   0.988   0.012 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000 82.3333
Fitness     Inf  0.0121  1.0000





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (1500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
  0.104   0.556   0.340 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.1871  0.3059
Neutral  5.3462  1.0000  1.6353
Fitness  3.2692  0.6115  1.0000


Posterior model probabilities (neuralnet):
Dayhoff Neutral Fitness 
 0.0002  0.9963  0.0035 

Bayes factors:
          Dayhoff   Neutral   Fitness
Dayhoff    1.0000    0.0002    0.0509
Neutral 5551.7780    1.0000  282.7367
Fitness   19.6359    0.0035    1.0000




Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (1500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.9973  0.0027 

Bayes factors:
         Dayhoff  Neutral  Fitness
Dayhoff            0.0000   0.0000
Neutral      Inf   1.0000 374.0000
Fitness      Inf   0.0027   1.0000





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (1500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
      0       1       0 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff               0        
Neutral     Inf       1     Inf
Fitness               0        





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (1500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0033  0.8700  0.1267 

Bayes factors:
         Dayhoff  Neutral  Fitness
Dayhoff   1.0000   0.0038   0.0263
Neutral 261.0000   1.0000   6.8684
Fitness  38.0000   0.1456   1.0000


Posterior model probabilities (neuralnet):
Dayhoff Neutral Fitness 
      0       1       0 

Bayes factors:
             Dayhoff      Neutral      Fitness
Dayhoff 1.000000e+00 0.000000e+00 5.500000e-03
Neutral 1.361331e+08 1.000000e+00 7.548658e+05
Fitness 1.803408e+02 0.000000e+00 1.000000e+00




Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (1500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
  0.000   0.994   0.006 

Bayes factors:
         Dayhoff  Neutral  Fitness
Dayhoff            0.0000   0.0000
Neutral      Inf   1.0000 165.6667
Fitness      Inf   0.0060   1.0000





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (1500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
      0       1       0 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff               0        
Neutral     Inf       1     Inf
Fitness               0        





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (1500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0167  0.7567  0.2267 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.0220  0.0735
Neutral 45.4000  1.0000  3.3382
Fitness 13.6000  0.2996  1.0000


Posterior model probabilities (neuralnet):
Dayhoff Neutral Fitness 
 0.0010  0.9836  0.0154 

Bayes factors:
          Dayhoff   Neutral   Fitness
Dayhoff    1.0000    0.0010    0.0634
Neutral 1008.3668    1.0000   63.8930
Fitness   15.7821    0.0157    1.0000




Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (1500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0007  0.8213  0.1780 

Bayes factors:
          Dayhoff   Neutral   Fitness
Dayhoff    1.0000    0.0008    0.0037
Neutral 1232.0000    1.0000    4.6142
Fitness  267.0000    0.2167    1.0000


Posterior model probabilities (neuralnet):
Dayhoff Neutral Fitness 
 0.0000  0.9999  0.0001 

Bayes factors:
            Dayhoff     Neutral     Fitness
Dayhoff      1.0000      0.0000      0.1389
Neutral 116419.1318      1.0000  16167.8713
Fitness      7.2006      0.0001      1.0000




Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (1500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.9493  0.0507 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000 18.7368
Fitness     Inf  0.0534  1.0000





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (1500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.9773  0.0227 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000 43.1176
Fitness     Inf  0.0232  1.0000





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (1500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.9993  0.0007 

Bayes factors:
          Dayhoff   Neutral   Fitness
Dayhoff              0.0000    0.0000
Neutral       Inf    1.0000 1499.0000
Fitness       Inf    0.0007    1.0000





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (1500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.9967  0.0033 

Bayes factors:
         Dayhoff  Neutral  Fitness
Dayhoff            0.0000   0.0000
Neutral      Inf   1.0000 299.0000
Fitness      Inf   0.0033   1.0000





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (1500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
      0       1       0 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff               0        
Neutral     Inf       1     Inf
Fitness               0        





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (1500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0140  0.7693  0.2167 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.0182  0.0646
Neutral 54.9524  1.0000  3.5508
Fitness 15.4762  0.2816  1.0000


Posterior model probabilities (neuralnet):
Dayhoff Neutral Fitness 
      0       1       0 

Bayes factors:
             Dayhoff      Neutral      Fitness
Dayhoff 1.000000e+00 0.000000e+00 2.200000e-03
Neutral 1.598123e+07 1.000000e+00 3.511294e+04
Fitness 4.551380e+02 0.000000e+00 1.000000e+00




Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (1500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
      0       1       0 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff               0        
Neutral     Inf       1     Inf
Fitness               0        





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (1500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.6353  0.3647 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  1.7422
Fitness     Inf  0.5740  1.0000





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (1500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
      0       1       0 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff               0        
Neutral     Inf       1     Inf
Fitness               0        





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (1500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.7573  0.2427 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  3.1209
Fitness     Inf  0.3204  1.0000





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (1500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
  0.000   0.996   0.004 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff           0.000   0.000
Neutral     Inf   1.000 249.000
Fitness     Inf   0.004   1.000





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (1500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.9187  0.0813 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000 11.2951
Fitness     Inf  0.0885  1.0000





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (1500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.9953  0.0047 

Bayes factors:
         Dayhoff  Neutral  Fitness
Dayhoff            0.0000   0.0000
Neutral      Inf   1.0000 213.2857
Fitness      Inf   0.0047   1.0000





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (1500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.7533  0.2467 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  3.0541
Fitness     Inf  0.3274  1.0000





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (1500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
  0.000   0.976   0.024 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000 40.6667
Fitness     Inf  0.0246  1.0000





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (1500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
  0.002   0.660   0.338 

Bayes factors:
         Dayhoff  Neutral  Fitness
Dayhoff   1.0000   0.0030   0.0059
Neutral 330.0000   1.0000   1.9527
Fitness 169.0000   0.5121   1.0000


Posterior model probabilities (neuralnet):
Dayhoff Neutral Fitness 
 0.0000  0.9999  0.0001 

Bayes factors:
            Dayhoff     Neutral     Fitness
Dayhoff      1.0000      0.0000      0.0124
Neutral 698733.2291      1.0000   8679.3875
Fitness     80.5049      0.0001      1.0000




Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (1500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.1593  0.5213  0.3193 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.3056  0.4990
Neutral  3.2720  1.0000  1.6326
Fitness  2.0042  0.6125  1.0000


Posterior model probabilities (neuralnet):
Dayhoff Neutral Fitness 
 0.0000  0.9998  0.0002 

Bayes factors:
           Dayhoff    Neutral    Fitness
Dayhoff     1.0000     0.0000     0.0815
Neutral 56014.5641     1.0000  4563.0551
Fitness    12.2757     0.0002     1.0000




Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (1500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
  0.130   0.484   0.386 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.2686  0.3368
Neutral  3.7231  1.0000  1.2539
Fitness  2.9692  0.7975  1.0000


Posterior model probabilities (neuralnet):
Dayhoff Neutral Fitness 
 0.0086  0.9518  0.0396 

Bayes factors:
         Dayhoff  Neutral  Fitness
Dayhoff   1.0000   0.0091   0.2183
Neutral 110.1298   1.0000  24.0449
Fitness   4.5802   0.0416   1.0000




Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (1500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
  0.000   0.968   0.032 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000 30.2500
Fitness     Inf  0.0331  1.0000





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (1500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.9993  0.0007 

Bayes factors:
          Dayhoff   Neutral   Fitness
Dayhoff              0.0000    0.0000
Neutral       Inf    1.0000 1499.0000
Fitness       Inf    0.0007    1.0000





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (1500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
      0       1       0 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff               0        
Neutral     Inf       1     Inf
Fitness               0        





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (1500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.9807  0.0193 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000 50.7241
Fitness     Inf  0.0197  1.0000





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (1500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
      0       1       0 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff               0        
Neutral     Inf       1     Inf
Fitness               0        





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (1500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
      0       1       0 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff               0        
Neutral     Inf       1     Inf
Fitness               0        





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (1500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
  0.000   0.996   0.004 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff           0.000   0.000
Neutral     Inf   1.000 249.000
Fitness     Inf   0.004   1.000





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (1500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.9613  0.0387 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000 24.8621
Fitness     Inf  0.0402  1.0000





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (1500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.9893  0.0107 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000 92.7500
Fitness     Inf  0.0108  1.0000





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (1500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
      0       1       0 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff               0        
Neutral     Inf       1     Inf
Fitness               0        





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (1500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
  0.000   0.998   0.002 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff           0.000   0.000
Neutral     Inf   1.000 499.000
Fitness     Inf   0.002   1.000





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (1500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.8987  0.1013 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  8.8684
Fitness     Inf  0.1128  1.0000





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (1500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.9547  0.0453 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000 21.0588
Fitness     Inf  0.0475  1.0000





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (1500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.9427  0.0573 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000 16.4419
Fitness     Inf  0.0608  1.0000





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (1500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
      0       1       0 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff               0        
Neutral     Inf       1     Inf
Fitness               0        





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (1500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
      0       1       0 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff               0        
Neutral     Inf       1     Inf
Fitness               0        





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (1500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0147  0.6120  0.3733 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.0240  0.0393
Neutral 41.7273  1.0000  1.6393
Fitness 25.4545  0.6100  1.0000


Posterior model probabilities (neuralnet):
Dayhoff Neutral Fitness 
 0.0000  0.9995  0.0005 

Bayes factors:
            Dayhoff     Neutral     Fitness
Dayhoff      1.0000      0.0000      0.0042
Neutral 495516.0481      1.0000   2066.3055
Fitness    239.8077      0.0005      1.0000




Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (1500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.1067  0.5827  0.3107 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.1831  0.3433
Neutral  5.4625  1.0000  1.8755
Fitness  2.9125  0.5332  1.0000


Posterior model probabilities (neuralnet):
Dayhoff Neutral Fitness 
      0       1       0 

Bayes factors:
             Dayhoff      Neutral      Fitness
Dayhoff 1.000000e+00 0.000000e+00 2.000000e-03
Neutral 2.056159e+07 1.000000e+00 4.068372e+04
Fitness 5.054009e+02 0.000000e+00 1.000000e+00




Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (1500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
      0       1       0 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff               0        
Neutral     Inf       1     Inf
Fitness               0        





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (1500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.9913  0.0087 

Bayes factors:
         Dayhoff  Neutral  Fitness
Dayhoff            0.0000   0.0000
Neutral      Inf   1.0000 114.3846
Fitness      Inf   0.0087   1.0000





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (1500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
      0       1       0 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff               0        
Neutral     Inf       1     Inf
Fitness               0        





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (1500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
      0       1       0 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff               0        
Neutral     Inf       1     Inf
Fitness               0        





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (1500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
  0.000   0.932   0.068 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000 13.7059
Fitness     Inf  0.0730  1.0000





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (1500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
      0       1       0 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff               0        
Neutral     Inf       1     Inf
Fitness               0        





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (1500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
      0       1       0 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff               0        
Neutral     Inf       1     Inf
Fitness               0        





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (1500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
      0       1       0 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff               0        
Neutral     Inf       1     Inf
Fitness               0        





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (1500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
      0       1       0 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff               0        
Neutral     Inf       1     Inf
Fitness               0        





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (1500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
      0       1       0 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff               0        
Neutral     Inf       1     Inf
Fitness               0        





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (1500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
      0       1       0 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff               0        
Neutral     Inf       1     Inf
Fitness               0        





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (1500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
  0.000   0.402   0.598 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.6722
Fitness     Inf  1.4876  1.0000





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (1500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
      0       1       0 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff               0        
Neutral     Inf       1     Inf
Fitness               0        





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (1500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
      0       1       0 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff               0        
Neutral     Inf       1     Inf
Fitness               0        





