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      97       0       3
Neutral       3      95       2
Fitness       2       1      97


Mean model posterior probabilities (neuralnet)

$tol0.005
        Dayhoff Neutral Fitness
Dayhoff  0.9417  0.0024  0.0560
Neutral  0.0207  0.9152  0.0641
Fitness  0.0296  0.0377  0.9326




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 (750 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 (750 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.7893  0.2107 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  3.7468
Fitness     Inf  0.2669  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 (750 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.9827  0.0173 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000 56.6923
Fitness     Inf  0.0176  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 (750 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 (750 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.9747  0.0253 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000 38.4737
Fitness     Inf  0.0260  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 (750 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0667  0.6853  0.2480 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.0973  0.2688
Neutral 10.2800  1.0000  2.7634
Fitness  3.7200  0.3619  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      0.0107
Neutral 484089.0933      1.0000   5201.8977
Fitness     93.0601      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 (750 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 (750 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 (750 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
  0.036   0.596   0.368 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.0604  0.0978
Neutral 16.5556  1.0000  1.6196
Fitness 10.2222  0.6174  1.0000


Posterior model probabilities (neuralnet):
Dayhoff Neutral Fitness 
 0.0016  0.9675  0.0309 

Bayes factors:
         Dayhoff  Neutral  Fitness
Dayhoff   1.0000   0.0016   0.0516
Neutral 606.3570   1.0000  31.2983
Fitness  19.3735   0.0320   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 (750 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 (750 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0560  0.6027  0.3413 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.0929  0.1641
Neutral 10.7619  1.0000  1.7656
Fitness  6.0952  0.5664  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      0.0100
Neutral 695256.0174      1.0000   6971.6822
Fitness     99.7257      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 (750 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.9707  0.0293 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000 33.0909
Fitness     Inf  0.0302  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 (750 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 (750 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.9907  0.0093 

Bayes factors:
         Dayhoff  Neutral  Fitness
Dayhoff            0.0000   0.0000
Neutral      Inf   1.0000 106.1429
Fitness      Inf   0.0094   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 (750 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 (750 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 (750 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 (750 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 (750 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 (750 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
   0.00    0.98    0.02 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000 49.0000
Fitness     Inf  0.0204  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 (750 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 (750 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 (750 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.2267  0.4467  0.3267 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.5075  0.6939
Neutral  1.9706  1.0000  1.3673
Fitness  1.4412  0.7313  1.0000


Posterior model probabilities (neuralnet):
Dayhoff Neutral Fitness 
 0.0000  0.9923  0.0077 

Bayes factors:
           Dayhoff    Neutral    Fitness
Dayhoff     1.0000     0.0000     0.0055
Neutral 23754.2537     1.0000   129.5744
Fitness   183.3252     0.0077     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 (750 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.8547  0.1453 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  5.8807
Fitness     Inf  0.1700  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 (750 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 (750 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 (750 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0253  0.7200  0.2547 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.0352  0.0995
Neutral 28.4211  1.0000  2.8272
Fitness 10.0526  0.3537  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      0.0171
Neutral 311876.9729      1.0000   5321.6639
Fitness     58.6052      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 (750 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0013  0.7453  0.2533 

Bayes factors:
         Dayhoff  Neutral  Fitness
Dayhoff   1.0000   0.0018   0.0053
Neutral 559.0000   1.0000   2.9421
Fitness 190.0000   0.3399   1.0000


Posterior model probabilities (neuralnet):
Dayhoff Neutral Fitness 
 0.0001  0.9959  0.0039 

Bayes factors:
          Dayhoff   Neutral   Fitness
Dayhoff    1.0000    0.0001    0.0377
Neutral 6737.0322    1.0000  254.0925
Fitness   26.5141    0.0039    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 (750 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 (750 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.9173  0.0827 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000 11.0968
Fitness     Inf  0.0901  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 (750 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 (750 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.9573  0.0427 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000 22.4375
Fitness     Inf  0.0446  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 (750 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0827  0.6107  0.3067 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.1354  0.2696
Neutral  7.3871  1.0000  1.9913
Fitness  3.7097  0.5022  1.0000


Posterior model probabilities (neuralnet):
Dayhoff Neutral Fitness 
 0.0000  0.9983  0.0016 

Bayes factors:
           Dayhoff    Neutral    Fitness
Dayhoff     1.0000     0.0000     0.0226
Neutral 26966.0956     1.0000   610.3752
Fitness    44.1795     0.0016     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 (750 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.9933  0.0067 

Bayes factors:
         Dayhoff  Neutral  Fitness
Dayhoff            0.0000   0.0000
Neutral      Inf   1.0000 149.0000
Fitness      Inf   0.0067   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 (750 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 (750 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 (750 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 (750 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 (750 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.2173  0.5027  0.2800 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.4324  0.7762
Neutral  2.3129  1.0000  1.7952
Fitness  1.2883  0.5570  1.0000


Posterior model probabilities (neuralnet):
Dayhoff Neutral Fitness 
 0.0001  0.9991  0.0008 

Bayes factors:
           Dayhoff    Neutral    Fitness
Dayhoff     1.0000     0.0001     0.0963
Neutral 12406.0263     1.0000  1194.7090
Fitness    10.3841     0.0008     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 (750 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
  0.188   0.436   0.376 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.4312  0.5000
Neutral  2.3191  1.0000  1.1596
Fitness  2.0000  0.8624  1.0000


Posterior model probabilities (neuralnet):
Dayhoff Neutral Fitness 
 0.0494  0.4754  0.4752 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.1040  0.1040
Neutral  9.6167  1.0000  1.0005
Fitness  9.6114  0.9995  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 (750 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.9227  0.0773 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000 11.9310
Fitness     Inf  0.0838  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 (750 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 (750 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0973  0.5507  0.3520 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.1768  0.2765
Neutral  5.6575  1.0000  1.5644
Fitness  3.6164  0.6392  1.0000


Posterior model probabilities (neuralnet):
Dayhoff Neutral Fitness 
 0.0000  0.9940  0.0059 

Bayes factors:
           Dayhoff    Neutral    Fitness
Dayhoff     1.0000     0.0000     0.0030
Neutral 55040.8417     1.0000   167.5422
Fitness   328.5193     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 (750 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 (750 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 (750 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0027  0.8560  0.1413 

Bayes factors:
         Dayhoff  Neutral  Fitness
Dayhoff   1.0000   0.0031   0.0189
Neutral 321.0000   1.0000   6.0566
Fitness  53.0000   0.1651   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      0.0347
Neutral 131830.0706      1.0000   4579.9020
Fitness     28.7845      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 (750 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 (750 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 (750 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0280  0.7227  0.2493 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.0387  0.1123
Neutral 25.8095  1.0000  2.8984
Fitness  8.9048  0.3450  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      0.0082
Neutral 259108.5787      1.0000   2112.7317
Fitness    122.6415      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 (750 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.8453  0.1547 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  5.4655
Fitness     Inf  0.1830  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 (750 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.9573  0.0427 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000 22.4375
Fitness     Inf  0.0446  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 (750 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.9787  0.0213 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000 45.8750
Fitness     Inf  0.0218  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 (750 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 (750 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 (750 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 (750 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0147  0.7720  0.2133 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.0190  0.0687
Neutral 52.6364  1.0000  3.6188
Fitness 14.5455  0.2763  1.0000


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

Bayes factors:
             Dayhoff      Neutral      Fitness
Dayhoff       1.0000       0.0000       0.0173
Neutral 4081931.9729       1.0000   70632.7967
Fitness      57.7909       0.0000       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 (750 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 (750 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
  0.000   0.592   0.408 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  1.4510
Fitness     Inf  0.6892  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 (750 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 (750 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.7787  0.2213 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  3.5181
Fitness     Inf  0.2842  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 (750 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 (750 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.9213  0.0787 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000 11.7119
Fitness     Inf  0.0854  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 (750 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 (750 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.7493  0.2507 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  2.9894
Fitness     Inf  0.3345  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 (750 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.9827  0.0173 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000 56.6923
Fitness     Inf  0.0176  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 (750 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0027  0.6773  0.3200 

Bayes factors:
         Dayhoff  Neutral  Fitness
Dayhoff   1.0000   0.0039   0.0083
Neutral 254.0000   1.0000   2.1167
Fitness 120.0000   0.4724   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     0.0792
Neutral 95970.3281     1.0000  7599.2853
Fitness    12.6289     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 (750 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.1547  0.5067  0.3387 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.3053  0.4567
Neutral  3.2759  1.0000  1.4961
Fitness  2.1897  0.6684  1.0000


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

Bayes factors:
            Dayhoff     Neutral     Fitness
Dayhoff      1.0000      0.0000      0.0135
Neutral 220305.3492      1.0000   2971.8437
Fitness     74.1309      0.0003      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 (750 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.1347  0.5333  0.3320 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.2525  0.4056
Neutral  3.9604  1.0000  1.6064
Fitness  2.4653  0.6225  1.0000


Posterior model probabilities (neuralnet):
Dayhoff Neutral Fitness 
 0.0011  0.9828  0.0161 

Bayes factors:
         Dayhoff  Neutral  Fitness
Dayhoff   1.0000   0.0011   0.0674
Neutral 905.6553   1.0000  61.0566
Fitness  14.8330   0.0164   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 (750 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 (750 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 (750 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 (750 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 (750 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 (750 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 (750 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 (750 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 (750 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.9907  0.0093 

Bayes factors:
         Dayhoff  Neutral  Fitness
Dayhoff            0.0000   0.0000
Neutral      Inf   1.0000 106.1429
Fitness      Inf   0.0094   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 (750 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 (750 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 (750 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 (750 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 (750 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.9387  0.0613 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000 15.3043
Fitness     Inf  0.0653  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 (750 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 (750 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 (750 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0147  0.6200  0.3653 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.0237  0.0401
Neutral 42.2727  1.0000  1.6971
Fitness 24.9091  0.5892  1.0000


Posterior model probabilities (neuralnet):
Dayhoff Neutral Fitness 
 0.0000  0.9989  0.0011 

Bayes factors:
           Dayhoff    Neutral    Fitness
Dayhoff     1.0000     0.0000     0.0116
Neutral 82083.4638     1.0000   948.2292
Fitness    86.5650     0.0011     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 (750 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0933  0.5973  0.3093 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.1562  0.3017
Neutral  6.4000  1.0000  1.9310
Fitness  3.3143  0.5179  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      0.0186
Neutral 680017.9956      1.0000  12646.0794
Fitness     53.7730      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 (750 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 (750 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 (750 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 (750 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 (750 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.9333  0.0667 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000 14.0000
Fitness     Inf  0.0714  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 (750 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 (750 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 (750 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 (750 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 (750 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 (750 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 (750 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
  0.000   0.376   0.624 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.6026
Fitness     Inf  1.6596  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 (750 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 (750 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        





