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

$tol0.01
        Dayhoff Neutral Fitness
Dayhoff      99       0       1
Neutral       0      99       1
Fitness       5       0      95


Mean model posterior probabilities (neuralnet)

$tol0.01
        Dayhoff Neutral Fitness
Dayhoff  0.9776  0.0005  0.0219
Neutral  0.0018  0.9343  0.0638
Fitness  0.0486  0.0325  0.9189




Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (300 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 (300 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
   0.00    0.66    0.34 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  1.9412
Fitness     Inf  0.5152  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 (300 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.9167  0.0833 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000 11.0000
Fitness     Inf  0.0909  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 (300 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
   0.00    0.99    0.01 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000 99.0000
Fitness     Inf  0.0101  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 (300 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.8967  0.1033 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  8.6774
Fitness     Inf  0.1152  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 (300 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.1267  0.5767  0.2967 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.2197  0.4270
Neutral  4.5526  1.0000  1.9438
Fitness  2.3421  0.5145  1.0000


Posterior model probabilities (neuralnet):
Dayhoff Neutral Fitness 
 0.0001  0.9998  0.0001 

Bayes factors:
           Dayhoff    Neutral    Fitness
Dayhoff     1.0000     0.0001     2.1431
Neutral  9024.9001     1.0000 19341.0410
Fitness     0.4666     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 (300 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

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

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000 41.8571
Fitness     Inf  0.0239  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 (300 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.9867  0.0133 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000 74.0000
Fitness     Inf  0.0135  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 (300 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0667  0.5533  0.3800 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.1205  0.1754
Neutral  8.3000  1.0000  1.4561
Fitness  5.7000  0.6867  1.0000


Posterior model probabilities (neuralnet):
Dayhoff Neutral Fitness 
 0.0002  0.9732  0.0266 

Bayes factors:
          Dayhoff   Neutral   Fitness
Dayhoff    1.0000    0.0002    0.0078
Neutral 4673.7693    1.0000   36.6027
Fitness  127.6891    0.0273    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 (300 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.9467  0.0533 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000 17.7500
Fitness     Inf  0.0563  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 (300 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.1167  0.5433  0.3400 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.2147  0.3431
Neutral  4.6571  1.0000  1.5980
Fitness  2.9143  0.6258  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      0.0147
Neutral 146823.0100      1.0000   2154.1312
Fitness     68.1588      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 (300 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.8467  0.1533 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  5.5217
Fitness     Inf  0.1811  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 (300 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 (300 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
   0.00    0.97    0.03 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000 32.3333
Fitness     Inf  0.0309  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 (300 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

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

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





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (300 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 (300 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.9733  0.0267 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000 36.5000
Fitness     Inf  0.0274  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 (300 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 (300 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 (300 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.9367  0.0633 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000 14.7895
Fitness     Inf  0.0676  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 (300 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 (300 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

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

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





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (300 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.3300  0.4033  0.2667 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.8182  1.2375
Neutral  1.2222  1.0000  1.5125
Fitness  0.8081  0.6612  1.0000


Posterior model probabilities (neuralnet):
Dayhoff Neutral Fitness 
 0.0002  0.9993  0.0005 

Bayes factors:
          Dayhoff   Neutral   Fitness
Dayhoff    1.0000    0.0002    0.3990
Neutral 4932.7023    1.0000 1968.2427
Fitness    2.5061    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 (300 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0133  0.7300  0.2567 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.0183  0.0519
Neutral 54.7500  1.0000  2.8442
Fitness 19.2500  0.3516  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      0.0102
Neutral 983424.4114      1.0000   9987.3469
Fitness     98.4670      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 (300 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
   0.00    0.99    0.01 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000 99.0000
Fitness     Inf  0.0101  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 (300 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.9867  0.0133 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000 74.0000
Fitness     Inf  0.0135  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 (300 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0500  0.5833  0.3667 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.0857  0.1364
Neutral 11.6667  1.0000  1.5909
Fitness  7.3333  0.6286  1.0000


Posterior model probabilities (neuralnet):
Dayhoff Neutral Fitness 
 0.0000  0.9996  0.0004 

Bayes factors:
            Dayhoff     Neutral     Fitness
Dayhoff      1.0000      0.0000      0.0071
Neutral 362395.3764      1.0000   2575.7502
Fitness    140.6951      0.0004      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 (300 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0033  0.6433  0.3533 

Bayes factors:
         Dayhoff  Neutral  Fitness
Dayhoff   1.0000   0.0052   0.0094
Neutral 193.0000   1.0000   1.8208
Fitness 106.0000   0.5492   1.0000


Posterior model probabilities (neuralnet):
Dayhoff Neutral Fitness 
 0.0001  0.9893  0.0106 

Bayes factors:
           Dayhoff    Neutral    Fitness
Dayhoff     1.0000     0.0001     0.0077
Neutral 12065.7201     1.0000    93.3922
Fitness   129.1941     0.0107     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 (300 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 (300 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.8067  0.1933 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  4.1724
Fitness     Inf  0.2397  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 (300 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.9733  0.0267 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000 36.5000
Fitness     Inf  0.0274  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 (300 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.9567  0.0433 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000 22.0769
Fitness     Inf  0.0453  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 (300 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.1400  0.5633  0.2967 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.2485  0.4719
Neutral  4.0238  1.0000  1.8989
Fitness  2.1190  0.5266  1.0000


Posterior model probabilities (neuralnet):
Dayhoff Neutral Fitness 
 0.0000  0.9996  0.0004 

Bayes factors:
           Dayhoff    Neutral    Fitness
Dayhoff     1.0000     0.0000     0.0577
Neutral 43460.2161     1.0000  2507.7453
Fitness    17.3304     0.0004     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 (300 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.9833  0.0167 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000 59.0000
Fitness     Inf  0.0169  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 (300 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.9733  0.0267 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000 36.5000
Fitness     Inf  0.0274  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 (300 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 (300 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.9867  0.0133 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000 74.0000
Fitness     Inf  0.0135  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 (300 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.8733  0.1267 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  6.8947
Fitness     Inf  0.1450  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 (300 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
   0.27    0.47    0.26 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.5745  1.0385
Neutral  1.7407  1.0000  1.8077
Fitness  0.9630  0.5532  1.0000


Posterior model probabilities (neuralnet):
Dayhoff Neutral Fitness 
 0.0019  0.9955  0.0026 

Bayes factors:
         Dayhoff  Neutral  Fitness
Dayhoff   1.0000   0.0019   0.7045
Neutral 537.4783   1.0000 378.6304
Fitness   1.4195   0.0026   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 (300 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
   0.27    0.37    0.36 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.7297  0.7500
Neutral  1.3704  1.0000  1.0278
Fitness  1.3333  0.9730  1.0000


Posterior model probabilities (neuralnet):
Dayhoff Neutral Fitness 
 0.0273  0.4524  0.5203 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.0603  0.0525
Neutral 16.5719  1.0000  0.8696
Fitness 19.0570  1.1500  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 (300 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
   0.00    0.82    0.18 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  4.5556
Fitness     Inf  0.2195  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 (300 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
   0.00    0.93    0.07 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000 13.2857
Fitness     Inf  0.0753  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 (300 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.1433  0.5033  0.3533 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.2848  0.4057
Neutral  3.5116  1.0000  1.4245
Fitness  2.4651  0.7020  1.0000


Posterior model probabilities (neuralnet):
Dayhoff Neutral Fitness 
 0.0014  0.9745  0.0241 

Bayes factors:
         Dayhoff  Neutral  Fitness
Dayhoff   1.0000   0.0014   0.0586
Neutral 689.6975   1.0000  40.4131
Fitness  17.0662   0.0247   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 (300 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 (300 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 (300 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0100  0.7667  0.2233 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.0130  0.0448
Neutral 76.6667  1.0000  3.4328
Fitness 22.3333  0.2913  1.0000


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

Bayes factors:
           Dayhoff    Neutral    Fitness
Dayhoff     1.0000     0.0000     0.0273
Neutral 28033.0557     1.0000   765.3235
Fitness    36.6290     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 (300 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 (300 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 (300 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0567  0.6667  0.2767 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.0850  0.2048
Neutral 11.7647  1.0000  2.4096
Fitness  4.8824  0.4150  1.0000


Posterior model probabilities (neuralnet):
Dayhoff Neutral Fitness 
 0.0001  0.9990  0.0009 

Bayes factors:
           Dayhoff    Neutral    Fitness
Dayhoff     1.0000     0.0001     0.0564
Neutral 18933.2421     1.0000  1068.2619
Fitness    17.7234     0.0009     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 (300 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0067  0.7133  0.2800 

Bayes factors:
         Dayhoff  Neutral  Fitness
Dayhoff   1.0000   0.0093   0.0238
Neutral 107.0000   1.0000   2.5476
Fitness  42.0000   0.3925   1.0000


Posterior model probabilities (neuralnet):
Dayhoff Neutral Fitness 
 0.0000  0.9993  0.0007 

Bayes factors:
           Dayhoff    Neutral    Fitness
Dayhoff     1.0000     0.0000     0.0408
Neutral 36054.8150     1.0000  1470.7344
Fitness    24.5148     0.0007     1.0000




Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (300 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
   0.00    0.85    0.15 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  5.6667
Fitness     Inf  0.1765  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 (300 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
   0.00    0.94    0.06 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000 15.6667
Fitness     Inf  0.0638  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 (300 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

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

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





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (300 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 (300 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 (300 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0200  0.6733  0.3067 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.0297  0.0652
Neutral 33.6667  1.0000  2.1957
Fitness 15.3333  0.4554  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       0.0027
Neutral 1733696.0123       1.0000    4712.2198
Fitness     367.9149       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 (300 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 (300 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.6133  0.3867 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  1.5862
Fitness     Inf  0.6304  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 (300 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 (300 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
   0.00    0.68    0.32 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  2.1250
Fitness     Inf  0.4706  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 (300 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.9567  0.0433 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000 22.0769
Fitness     Inf  0.0453  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 (300 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.8767  0.1233 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  7.1081
Fitness     Inf  0.1407  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 (300 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.9733  0.0267 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000 36.5000
Fitness     Inf  0.0274  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 (300 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.6867  0.3133 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  2.1915
Fitness     Inf  0.4563  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 (300 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.9467  0.0533 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000 17.7500
Fitness     Inf  0.0563  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 (300 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0033  0.6600  0.3367 

Bayes factors:
         Dayhoff  Neutral  Fitness
Dayhoff   1.0000   0.0051   0.0099
Neutral 198.0000   1.0000   1.9604
Fitness 101.0000   0.5101   1.0000


Posterior model probabilities (neuralnet):
Dayhoff Neutral Fitness 
 0.0002  0.9705  0.0293 

Bayes factors:
          Dayhoff   Neutral   Fitness
Dayhoff    1.0000    0.0002    0.0067
Neutral 4936.4415    1.0000   33.0781
Fitness  149.2358    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 (300 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.2100  0.4533  0.3367 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.4632  0.6238
Neutral  2.1587  1.0000  1.3465
Fitness  1.6032  0.7426  1.0000


Posterior model probabilities (neuralnet):
Dayhoff Neutral Fitness 
  0.000   0.999   0.001 

Bayes factors:
           Dayhoff    Neutral    Fitness
Dayhoff     1.0000     0.0000     0.0417
Neutral 25166.1676     1.0000  1050.5534
Fitness    23.9552     0.0010     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 (300 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.2333  0.4767  0.2900 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.4895  0.8046
Neutral  2.0429  1.0000  1.6437
Fitness  1.2429  0.6084  1.0000


Posterior model probabilities (neuralnet):
Dayhoff Neutral Fitness 
 0.0102  0.9770  0.0128 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.0105  0.7980
Neutral 95.5744  1.0000 76.2689
Fitness  1.2531  0.0131  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 (300 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
   0.00    0.95    0.05 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000 19.0000
Fitness     Inf  0.0526  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 (300 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
   0.00    0.96    0.04 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000 24.0000
Fitness     Inf  0.0417  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 (300 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 (300 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.9233  0.0767 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000 12.0435
Fitness     Inf  0.0830  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 (300 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 (300 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
   0.00    0.99    0.01 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000 99.0000
Fitness     Inf  0.0101  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 (300 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.9867  0.0133 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000 74.0000
Fitness     Inf  0.0135  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 (300 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
   0.00    0.91    0.09 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000 10.1111
Fitness     Inf  0.0989  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 (300 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 (300 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 (300 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 (300 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.8267  0.1733 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  4.7692
Fitness     Inf  0.2097  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 (300 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.8467  0.1533 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  5.5217
Fitness     Inf  0.1811  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 (300 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
    0.0     0.8     0.2 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff            0.00    0.00
Neutral     Inf    1.00    4.00
Fitness     Inf    0.25    1.00





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 (300 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 (300 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 (300 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0300  0.5333  0.4367 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.0562  0.0687
Neutral 17.7778  1.0000  1.2214
Fitness 14.5556  0.8188  1.0000


Posterior model probabilities (neuralnet):
Dayhoff Neutral Fitness 
 0.0001  0.9941  0.0058 

Bayes factors:
          Dayhoff   Neutral   Fitness
Dayhoff    1.0000    0.0001    0.0192
Neutral 8939.9791    1.0000  171.7884
Fitness   52.0406    0.0058    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 (300 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.1467  0.5700  0.2833 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.2573  0.5176
Neutral  3.8864  1.0000  2.0118
Fitness  1.9318  0.4971  1.0000


Posterior model probabilities (neuralnet):
Dayhoff Neutral Fitness 
 0.0001  0.9998  0.0001 

Bayes factors:
           Dayhoff    Neutral    Fitness
Dayhoff     1.0000     0.0001     0.9627
Neutral 10991.7192     1.0000 10581.7347
Fitness     1.0387     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 (300 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 (300 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
   0.00    0.93    0.07 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000 13.2857
Fitness     Inf  0.0753  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 (300 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 (300 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 (300 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.8833  0.1167 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  7.5714
Fitness     Inf  0.1321  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 (300 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 (300 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 (300 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 (300 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 (300 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 (300 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 (300 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.3633  0.6367 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.5707
Fitness     Inf  1.7523  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 (300 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 (300 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        





