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

$tol0.05
        Dayhoff Neutral Fitness
Dayhoff      98       1       1
Neutral       0      94       6
Fitness       1       1      98


Mean model posterior probabilities (neuralnet)

$tol0.05
        Dayhoff Neutral Fitness
Dayhoff  0.9718  0.0069  0.0213
Neutral  0.0054  0.8408  0.1539
Fitness  0.0230  0.1164  0.8606




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 (15000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.3503  0.2372  0.4125 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  1.4770  0.8494
Neutral  0.6771  1.0000  0.5751
Fitness  1.1774  1.7389  1.0000


Posterior model probabilities (neuralnet):
Dayhoff Neutral Fitness 
 0.8825  0.0144  0.1032 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000 61.3663  8.5537
Neutral  0.0163  1.0000  0.1394
Fitness  0.1169  7.1742  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 (15000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

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

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff       1     Inf     Inf
Neutral       0                
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 (15000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.4413  0.0027  0.5561 

Bayes factors:
         Dayhoff  Neutral  Fitness
Dayhoff   1.0000 165.4750   0.7935
Neutral   0.0060   1.0000   0.0048
Fitness   1.2602 208.5250   1.0000


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

Bayes factors:
             Dayhoff      Neutral      Fitness
Dayhoff 1.000000e+00 2.528270e+12 7.040321e+06
Neutral 0.000000e+00 1.000000e+00 0.000000e+00
Fitness 0.000000e+00 3.591130e+05 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 (15000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

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

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff       1     Inf     Inf
Neutral       0                
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 (15000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

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

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff       1     Inf     Inf
Neutral       0                
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 (15000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.9767  0.0000  0.0233 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000     Inf 41.9799
Neutral  0.0000          0.0000
Fitness  0.0238     Inf  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 (15000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

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

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff       1     Inf     Inf
Neutral       0                
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 (15000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.9865  0.0000  0.0135 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000     Inf 73.2574
Neutral  0.0000          0.0000
Fitness  0.0137     Inf  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 (15000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

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

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff       1     Inf     Inf
Neutral       0                
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 (15000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

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

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff       1     Inf     Inf
Neutral       0                
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 (15000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

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

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff       1     Inf     Inf
Neutral       0                
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 (15000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

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

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff       1     Inf     Inf
Neutral       0                
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 (15000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.9609  0.0000  0.0391 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000     Inf 24.5537
Neutral  0.0000          0.0000
Fitness  0.0407     Inf  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 (15000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.5277  0.0764  0.3959 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  6.9075  1.3331
Neutral  0.1448  1.0000  0.1930
Fitness  0.7501  5.1815  1.0000


Posterior model probabilities (neuralnet):
Dayhoff Neutral Fitness 
 0.9637  0.0023  0.0339 

Bayes factors:
         Dayhoff  Neutral  Fitness
Dayhoff   1.0000 410.5197  28.3891
Neutral   0.0024   1.0000   0.0692
Fitness   0.0352  14.4605   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 (15000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
  0.272   0.380   0.348 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.7158  0.7816
Neutral  1.3971  1.0000  1.0920
Fitness  1.2794  0.9158  1.0000


Posterior model probabilities (neuralnet):
Dayhoff Neutral Fitness 
 0.2196  0.0000  0.7804 

Bayes factors:
            Dayhoff     Neutral     Fitness
Dayhoff      1.0000  59349.4700      0.2814
Neutral      0.0000      1.0000      0.0000
Fitness      3.5541 210936.1753      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 (15000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.8877  0.0001  0.1123 

Bayes factors:
           Dayhoff    Neutral    Fitness
Dayhoff     1.0000 13315.0000     7.9068
Neutral     0.0001     1.0000     0.0006
Fitness     0.1265  1684.0000     1.0000


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

Bayes factors:
             Dayhoff      Neutral      Fitness
Dayhoff 1.000000e+00 5.134151e+07 1.958081e+05
Neutral 0.000000e+00 1.000000e+00 3.800000e-03
Fitness 0.000000e+00 2.622032e+02 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 (15000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

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

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff       1     Inf     Inf
Neutral       0                
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 (15000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

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

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff       1     Inf     Inf
Neutral       0                
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 (15000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

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

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff       1     Inf     Inf
Neutral       0                
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 (15000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

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

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff       1     Inf     Inf
Neutral       0                
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 (15000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

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

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff       1     Inf     Inf
Neutral       0                
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 (15000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

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

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff       1     Inf     Inf
Neutral       0                
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 (15000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

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

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff       1     Inf     Inf
Neutral       0                
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 (15000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

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

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff       1     Inf     Inf
Neutral       0                
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 (15000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.4937  0.0057  0.5006 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000 87.1294  0.9863
Neutral  0.0115  1.0000  0.0113
Fitness  1.0139 88.3412  1.0000


Posterior model probabilities (neuralnet):
Dayhoff Neutral Fitness 
 0.9220  0.0002  0.0778 

Bayes factors:
          Dayhoff   Neutral   Fitness
Dayhoff    1.0000 3789.8465   11.8524
Neutral    0.0003    1.0000    0.0031
Fitness    0.0844  319.7546    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 (15000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

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

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff       1     Inf     Inf
Neutral       0                
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 (15000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

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

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff       1     Inf     Inf
Neutral       0                
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 (15000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

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

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff       1     Inf     Inf
Neutral       0                
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 (15000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

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

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff       1     Inf     Inf
Neutral       0                
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 (15000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.8097  0.0004  0.1899 

Bayes factors:
          Dayhoff   Neutral   Fitness
Dayhoff    1.0000 2024.1667    4.2629
Neutral    0.0005    1.0000    0.0021
Fitness    0.2346  474.8333    1.0000


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

Bayes factors:
             Dayhoff      Neutral      Fitness
Dayhoff 1.000000e+00 1.072947e+07 1.559944e+04
Neutral 0.000000e+00 1.000000e+00 1.500000e-03
Fitness 1.000000e-04 6.878111e+02 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 (15000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

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

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff       1     Inf     Inf
Neutral       0                
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 (15000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.9921  0.0000  0.0079 

Bayes factors:
         Dayhoff  Neutral  Fitness
Dayhoff   1.0000      Inf 125.0504
Neutral   0.0000            0.0000
Fitness   0.0080      Inf   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 (15000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

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

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff       1     Inf     Inf
Neutral       0                
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 (15000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

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

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff       1     Inf     Inf
Neutral       0                
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 (15000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

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

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff       1     Inf     Inf
Neutral       0                
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 (15000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

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

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff       1     Inf     Inf
Neutral       0                
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 (15000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.8735  0.0001  0.1263 

Bayes factors:
          Dayhoff   Neutral   Fitness
Dayhoff    1.0000 6551.5000    6.9145
Neutral    0.0002    1.0000    0.0011
Fitness    0.1446  947.5000    1.0000


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

Bayes factors:
             Dayhoff      Neutral      Fitness
Dayhoff 1.000000e+00 6.361398e+07 3.808494e+05
Neutral 0.000000e+00 1.000000e+00 6.000000e-03
Fitness 0.000000e+00 1.670319e+02 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 (15000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.5465  0.0139  0.4396 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000 39.2201  1.2431
Neutral  0.0255  1.0000  0.0317
Fitness  0.8044 31.5502  1.0000


Posterior model probabilities (neuralnet):
Dayhoff Neutral Fitness 
 0.9987  0.0000  0.0013 

Bayes factors:
             Dayhoff      Neutral      Fitness
Dayhoff 1.000000e+00 7.337788e+07 7.537879e+02
Neutral 0.000000e+00 1.000000e+00 0.000000e+00
Fitness 1.300000e-03 9.734552e+04 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 (15000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

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

Bayes factors:
          Dayhoff   Neutral   Fitness
Dayhoff    1.0000       Inf 1499.0000
Neutral    0.0000              0.0000
Fitness    0.0007       Inf    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 (15000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

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

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff       1     Inf     Inf
Neutral       0                
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 (15000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.9365  0.0000  0.0635 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000     Inf 14.7398
Neutral  0.0000          0.0000
Fitness  0.0678     Inf  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 (15000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.7159  0.0002  0.2839 

Bayes factors:
          Dayhoff   Neutral   Fitness
Dayhoff    1.0000 3579.6667    2.5221
Neutral    0.0003    1.0000    0.0007
Fitness    0.3965 1419.3333    1.0000


Posterior model probabilities (neuralnet):
Dayhoff Neutral Fitness 
 0.9708  0.0000  0.0292 

Bayes factors:
           Dayhoff    Neutral    Fitness
Dayhoff     1.0000 88264.4513    33.2056
Neutral     0.0000     1.0000     0.0004
Fitness     0.0301  2658.1223     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 (15000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.9581  0.0000  0.0419 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000     Inf 22.8474
Neutral  0.0000          0.0000
Fitness  0.0438     Inf  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 (15000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

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

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff       1     Inf     Inf
Neutral       0                
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 (15000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.9999  0.0000  0.0001 

Bayes factors:
           Dayhoff    Neutral    Fitness
Dayhoff     1.0000        Inf 14999.0000
Neutral     0.0000                0.0000
Fitness     0.0001        Inf     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 (15000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

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

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff       1     Inf     Inf
Neutral       0                
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 (15000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

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

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff       1     Inf     Inf
Neutral       0                
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 (15000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

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

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff       1     Inf     Inf
Neutral       0                
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 (15000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

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

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff       1     Inf     Inf
Neutral       0                
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 (15000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

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

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff       1     Inf     Inf
Neutral       0                
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 (15000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.2569  0.4010  0.3421 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.6407  0.7511
Neutral  1.5607  1.0000  1.1723
Fitness  1.3313  0.8530  1.0000


Posterior model probabilities (neuralnet):
Dayhoff Neutral Fitness 
 0.4416  0.0086  0.5499 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000 51.6161  0.8030
Neutral  0.0194  1.0000  0.0156
Fitness  1.2453 64.2754  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 (15000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

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

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff       1     Inf     Inf
Neutral       0                
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 (15000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

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

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff       1     Inf     Inf
Neutral       0                
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 (15000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.9897  0.0000  0.0103 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000     Inf 96.4026
Neutral  0.0000          0.0000
Fitness  0.0104     Inf  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 (15000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

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

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff       1     Inf     Inf
Neutral       0                
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 (15000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.4446  0.1667  0.3887 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  2.6665  1.1439
Neutral  0.3750  1.0000  0.4290
Fitness  0.8742  2.3311  1.0000


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

Bayes factors:
             Dayhoff      Neutral      Fitness
Dayhoff 1.000000e+00 3.403794e+07 1.346286e+05
Neutral 0.000000e+00 1.000000e+00 4.000000e-03
Fitness 0.000000e+00 2.528285e+02 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 (15000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.2143  0.1325  0.6532 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  1.6167  0.3280
Neutral  0.6185  1.0000  0.2029
Fitness  3.0485  4.9286  1.0000


Posterior model probabilities (neuralnet):
Dayhoff Neutral Fitness 
 0.9891  0.0000  0.0109 

Bayes factors:
             Dayhoff      Neutral      Fitness
Dayhoff 1.000000e+00 1.342226e+08 9.086810e+01
Neutral 0.000000e+00 1.000000e+00 0.000000e+00
Fitness 1.100000e-02 1.477115e+06 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 (15000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

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

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff       1     Inf     Inf
Neutral       0                
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 (15000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

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

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff       1     Inf     Inf
Neutral       0                
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 (15000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

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

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff       1     Inf     Inf
Neutral       0                
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 (15000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.7909  0.0010  0.2081 

Bayes factors:
         Dayhoff  Neutral  Fitness
Dayhoff   1.0000 790.9333   3.8013
Neutral   0.0013   1.0000   0.0048
Fitness   0.2631 208.0667   1.0000


Posterior model probabilities (neuralnet):
Dayhoff Neutral Fitness 
 0.9889  0.0000  0.0111 

Bayes factors:
           Dayhoff    Neutral    Fitness
Dayhoff     1.0000 34168.3489    89.3452
Neutral     0.0000     1.0000     0.0026
Fitness     0.0112   382.4305     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 (15000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

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

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff       1     Inf     Inf
Neutral       0                
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 (15000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.9999  0.0000  0.0001 

Bayes factors:
           Dayhoff    Neutral    Fitness
Dayhoff     1.0000        Inf 14999.0000
Neutral     0.0000                0.0000
Fitness     0.0001        Inf     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 (15000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

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

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff       1     Inf     Inf
Neutral       0                
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 (15000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.2415  0.3869  0.3716 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.6243  0.6500
Neutral  1.6017  1.0000  1.0411
Fitness  1.5385  0.9605  1.0000


Posterior model probabilities (neuralnet):
Dayhoff Neutral Fitness 
 0.0996  0.0080  0.8924 

Bayes factors:
         Dayhoff  Neutral  Fitness
Dayhoff   1.0000  12.3944   0.1116
Neutral   0.0807   1.0000   0.0090
Fitness   8.9634 111.0958   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 (15000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

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

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff       1     Inf     Inf
Neutral       0                
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 (15000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

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

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff       1     Inf     Inf
Neutral       0                
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 (15000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

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

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff       1     Inf     Inf
Neutral       0                
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 (15000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

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

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff       1     Inf     Inf
Neutral       0                
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 (15000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

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

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff       1     Inf     Inf
Neutral       0                
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 (15000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

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

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff       1     Inf     Inf
Neutral       0                
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 (15000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

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

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff       1     Inf     Inf
Neutral       0                
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 (15000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

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

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff       1     Inf     Inf
Neutral       0                
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 (15000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.2576  0.3963  0.3461 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.6500  0.7444
Neutral  1.5386  1.0000  1.1453
Fitness  1.3434  0.8732  1.0000


Posterior model probabilities (neuralnet):
Dayhoff Neutral Fitness 
 0.4180  0.1202  0.4619 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  3.4789  0.9050
Neutral  0.2874  1.0000  0.2602
Fitness  1.1049  3.8439  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 (15000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

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

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff       1     Inf     Inf
Neutral       0                
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 (15000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

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

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff       1     Inf     Inf
Neutral       0                
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 (15000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

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

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff       1     Inf     Inf
Neutral       0                
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 (15000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.4669  0.0093  0.5239 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000 50.3813  0.8912
Neutral  0.0198  1.0000  0.0177
Fitness  1.1221 56.5324  1.0000


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

Bayes factors:
             Dayhoff      Neutral      Fitness
Dayhoff 1.000000e+00 5.790067e+07 1.169248e+04
Neutral 0.000000e+00 1.000000e+00 2.000000e-04
Fitness 1.000000e-04 4.951959e+03 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 (15000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

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

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff       1     Inf     Inf
Neutral       0                
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 (15000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

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

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff       1     Inf     Inf
Neutral       0                
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 (15000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
  0.833   0.000   0.167 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000     Inf  4.9880
Neutral  0.0000          0.0000
Fitness  0.2005     Inf  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 (15000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

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

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff       1     Inf     Inf
Neutral       0                
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 (15000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

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

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff       1     Inf     Inf
Neutral       0                
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 (15000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

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

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff       1     Inf     Inf
Neutral       0                
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 (15000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.9282  0.0000  0.0718 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000     Inf 12.9276
Neutral  0.0000          0.0000
Fitness  0.0774     Inf  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 (15000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

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

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff       1     Inf     Inf
Neutral       0                
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 (15000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

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

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff       1     Inf     Inf
Neutral       0                
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 (15000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

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

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff       1     Inf     Inf
Neutral       0                
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 (15000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

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

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff       1     Inf     Inf
Neutral       0                
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 (15000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

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

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff       1     Inf     Inf
Neutral       0                
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 (15000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.9991  0.0000  0.0009 

Bayes factors:
          Dayhoff   Neutral   Fitness
Dayhoff    1.0000       Inf 1070.4286
Neutral    0.0000              0.0000
Fitness    0.0009       Inf    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 (15000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.5269  0.0632  0.4099 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  8.3376  1.2856
Neutral  0.1199  1.0000  0.1542
Fitness  0.7778  6.4852  1.0000


Posterior model probabilities (neuralnet):
Dayhoff Neutral Fitness 
 0.9974  0.0000  0.0026 

Bayes factors:
             Dayhoff      Neutral      Fitness
Dayhoff 1.000000e+00 5.949976e+07 3.889846e+02
Neutral 0.000000e+00 1.000000e+00 0.000000e+00
Fitness 2.600000e-03 1.529617e+05 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 (15000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

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

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff       1     Inf     Inf
Neutral       0                
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 (15000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

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

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff       1     Inf     Inf
Neutral       0                
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 (15000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

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

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff       1     Inf     Inf
Neutral       0                
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 (15000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

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

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff       1     Inf     Inf
Neutral       0                
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 (15000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

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

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff       1     Inf     Inf
Neutral       0                
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 (15000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.9837  0.0000  0.0163 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000     Inf 60.4754
Neutral  0.0000          0.0000
Fitness  0.0165     Inf  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 (15000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.4545  0.1107  0.4347 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  4.1048  1.0455
Neutral  0.2436  1.0000  0.2547
Fitness  0.9564  3.9259  1.0000


Posterior model probabilities (neuralnet):
Dayhoff Neutral Fitness 
 0.9997  0.0000  0.0003 

Bayes factors:
             Dayhoff      Neutral      Fitness
Dayhoff 1.000000e+00 7.799372e+09 3.581506e+03
Neutral 0.000000e+00 1.000000e+00 0.000000e+00
Fitness 3.000000e-04 2.177680e+06 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 (15000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.9975  0.0001  0.0025 

Bayes factors:
           Dayhoff    Neutral    Fitness
Dayhoff     1.0000 14962.0000   404.3784
Neutral     0.0001     1.0000     0.0270
Fitness     0.0025    37.0000     1.0000


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

Bayes factors:
             Dayhoff      Neutral      Fitness
Dayhoff       1.0000 2690796.8543  790252.6696
Neutral       0.0000       1.0000       0.2937
Fitness       0.0000       3.4050       1.0000




