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

$tol0.05
        Dayhoff Neutral Fitness
Dayhoff      90       2       8
Neutral       0      97       3
Fitness       6       2      92


Mean model posterior probabilities (neuralnet)

$tol0.05
        Dayhoff Neutral Fitness
Dayhoff  0.9099  0.0120  0.0781
Neutral  0.0009  0.8630  0.1361
Fitness  0.0758  0.1054  0.8188




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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
  0.000   0.082   0.918 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.0893
Fitness     Inf 11.1951  1.0000





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.2627  0.3913  0.3460 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.6712  0.7592
Neutral  1.4898  1.0000  1.1310
Fitness  1.3173  0.8842  1.0000


Posterior model probabilities (neuralnet):
Dayhoff Neutral Fitness 
 0.0062  0.0000  0.9938 

Bayes factors:
            Dayhoff     Neutral     Fitness
Dayhoff      1.0000    902.4603      0.0063
Neutral      0.0011      1.0000      0.0000
Fitness    159.9434 144342.5409      1.0000




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

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

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.1152
Fitness     Inf  8.6774  1.0000





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.1313  0.8687 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.1512
Fitness     Inf  6.6142  1.0000





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.3553  0.6447 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.5512
Fitness     Inf  1.8143  1.0000





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.1373  0.8627 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.1592
Fitness     Inf  6.2816  1.0000





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

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

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.0830
Fitness     Inf 12.0435  1.0000





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.0367  0.9633 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.0381
Fitness     Inf 26.2727  1.0000





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0153  0.0867  0.8980 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.1769  0.0171
Neutral  5.6522  1.0000  0.0965
Fitness 58.5652 10.3615  1.0000


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

Bayes factors:
            Dayhoff     Neutral     Fitness
Dayhoff      1.0000     12.6200      0.0001
Neutral      0.0792      1.0000      0.0000
Fitness  10642.5157 134308.6906      1.0000




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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0020  0.3093  0.6887 

Bayes factors:
         Dayhoff  Neutral  Fitness
Dayhoff   1.0000   0.0065   0.0029
Neutral 154.6667   1.0000   0.4492
Fitness 344.3333   2.2263   1.0000


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

Bayes factors:
           Dayhoff    Neutral    Fitness
Dayhoff     1.0000     1.0824     0.0000
Neutral     0.9239     1.0000     0.0000
Fitness 23278.5448 25196.0095     1.0000




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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.2793  0.3987  0.3220 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.7007  0.8675
Neutral  1.4272  1.0000  1.2381
Fitness  1.1527  0.8077  1.0000


Posterior model probabilities (neuralnet):
Dayhoff Neutral Fitness 
 0.0968  0.0000  0.9032 

Bayes factors:
            Dayhoff     Neutral     Fitness
Dayhoff      1.0000  30926.0324      0.1072
Neutral      0.0000      1.0000      0.0000
Fitness      9.3319 288597.8135      1.0000




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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
  0.000   0.232   0.768 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.3021
Fitness     Inf  3.3103  1.0000





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.0733  0.9267 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.0791
Fitness     Inf 12.6364  1.0000





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

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

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.0169
Fitness     Inf 59.0000  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 (1500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.2247  0.7753 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.2898
Fitness     Inf  3.4510  1.0000





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.3147  0.6853 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.4591
Fitness     Inf  2.1780  1.0000





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0280  0.4813  0.4907 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.0582  0.0571
Neutral 17.1905  1.0000  0.9810
Fitness 17.5238  1.0194  1.0000


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

Bayes factors:
           Dayhoff    Neutral    Fitness
Dayhoff     1.0000     1.6493     0.0001
Neutral     0.6063     1.0000     0.0000
Fitness 13430.4364 22150.5477     1.0000




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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.2607  0.3907  0.3487 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.6672  0.7476
Neutral  1.4987  1.0000  1.1205
Fitness  1.3376  0.8925  1.0000


Posterior model probabilities (neuralnet):
Dayhoff Neutral Fitness 
 0.0617  0.0000  0.9383 

Bayes factors:
             Dayhoff      Neutral      Fitness
Dayhoff       1.0000  129435.8907       0.0657
Neutral       0.0000       1.0000       0.0000
Fitness      15.2174 1969681.2883       1.0000




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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0120  0.4233  0.5647 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.0283  0.0213
Neutral 35.2778  1.0000  0.7497
Fitness 47.0556  1.3339  1.0000


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

Bayes factors:
            Dayhoff     Neutral     Fitness
Dayhoff      1.0000      5.8294      0.0000
Neutral      0.1715      1.0000      0.0000
Fitness  28397.3592 165540.2875      1.0000




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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
  0.056   0.488   0.456 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.1148  0.1228
Neutral  8.7143  1.0000  1.0702
Fitness  8.1429  0.9344  1.0000


Posterior model probabilities (neuralnet):
Dayhoff Neutral Fitness 
 0.0001  0.0003  0.9996 

Bayes factors:
           Dayhoff    Neutral    Fitness
Dayhoff     1.0000     0.3713     0.0001
Neutral     2.6936     1.0000     0.0003
Fitness 10223.8577  3795.6783     1.0000




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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.0447  0.9553 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.0468
Fitness     Inf 21.3881  1.0000





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.1180  0.4667  0.4153 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.2529  0.2841
Neutral  3.9548  1.0000  1.1236
Fitness  3.5198  0.8900  1.0000


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

Bayes factors:
           Dayhoff    Neutral    Fitness
Dayhoff     1.0000     4.9562     0.0002
Neutral     0.2018     1.0000     0.0000
Fitness  5803.4468 28763.0533     1.0000




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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
  0.000   0.034   0.966 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.0352
Fitness     Inf 28.4118  1.0000





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.2567  0.4133  0.3300 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.6210  0.7778
Neutral  1.6104  1.0000  1.2525
Fitness  1.2857  0.7984  1.0000


Posterior model probabilities (neuralnet):
Dayhoff Neutral Fitness 
 0.1327  0.4962  0.3712 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.2674  0.3574
Neutral  3.7401  1.0000  1.3368
Fitness  2.7978  0.7480  1.0000




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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
  0.000   0.022   0.978 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.0225
Fitness     Inf 44.4545  1.0000





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.0247  0.9753 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.0253
Fitness     Inf 39.5405  1.0000





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0007  0.0613  0.9380 

Bayes factors:
          Dayhoff   Neutral   Fitness
Dayhoff    1.0000    0.0109    0.0007
Neutral   92.0000    1.0000    0.0654
Fitness 1407.0000   15.2935    1.0000


Posterior model probabilities (neuralnet):
Dayhoff Neutral Fitness 
 0.0002  0.0003  0.9995 

Bayes factors:
          Dayhoff   Neutral   Fitness
Dayhoff    1.0000    0.6501    0.0002
Neutral    1.5382    1.0000    0.0003
Fitness 5432.9344 3532.0496    1.0000




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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
  0.000   0.396   0.604 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.6556
Fitness     Inf  1.5253  1.0000





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0027  0.3547  0.6427 

Bayes factors:
         Dayhoff  Neutral  Fitness
Dayhoff   1.0000   0.0075   0.0041
Neutral 133.0000   1.0000   0.5519
Fitness 241.0000   1.8120   1.0000


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

Bayes factors:
           Dayhoff    Neutral    Fitness
Dayhoff     1.0000     2.1935     0.0000
Neutral     0.4559     1.0000     0.0000
Fitness 37856.8265 83039.7739     1.0000




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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.1833  0.4333  0.3833 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.4231  0.4783
Neutral  2.3636  1.0000  1.1304
Fitness  2.0909  0.8846  1.0000


Posterior model probabilities (neuralnet):
Dayhoff Neutral Fitness 
 0.0024  0.0014  0.9962 

Bayes factors:
         Dayhoff  Neutral  Fitness
Dayhoff   1.0000   1.7684   0.0024
Neutral   0.5655   1.0000   0.0014
Fitness 410.9854 726.7865   1.0000




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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.2547  0.3887  0.3567 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.6552  0.7140
Neutral  1.5262  1.0000  1.0897
Fitness  1.4005  0.9177  1.0000


Posterior model probabilities (neuralnet):
Dayhoff Neutral Fitness 
 0.1818  0.0001  0.8181 

Bayes factors:
           Dayhoff    Neutral    Fitness
Dayhoff     1.0000  2474.2314     0.2222
Neutral     0.0004     1.0000     0.0001
Fitness     4.5002 11134.4529     1.0000




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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.2173  0.7827 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.2777
Fitness     Inf  3.6012  1.0000





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.2720  0.4067  0.3213 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.6689  0.8465
Neutral  1.4951  1.0000  1.2656
Fitness  1.1814  0.7902  1.0000


Posterior model probabilities (neuralnet):
Dayhoff Neutral Fitness 
 0.4756  0.0024  0.5220 

Bayes factors:
         Dayhoff  Neutral  Fitness
Dayhoff   1.0000 197.0658   0.9110
Neutral   0.0051   1.0000   0.0046
Fitness   1.0977 216.3154   1.0000




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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.2693  0.4087  0.3220 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.6591  0.8364
Neutral  1.5173  1.0000  1.2692
Fitness  1.1955  0.7879  1.0000


Posterior model probabilities (neuralnet):
Dayhoff Neutral Fitness 
 0.3506  0.0065  0.6429 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000 54.1340  0.5453
Neutral  0.0185  1.0000  0.0101
Fitness  1.8339 99.2770  1.0000




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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.2087  0.7913 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.2637
Fitness     Inf  3.7923  1.0000





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
  0.004   0.444   0.552 

Bayes factors:
         Dayhoff  Neutral  Fitness
Dayhoff   1.0000   0.0090   0.0072
Neutral 111.0000   1.0000   0.8043
Fitness 138.0000   1.2432   1.0000


Posterior model probabilities (neuralnet):
Dayhoff Neutral Fitness 
 0.0003  0.0141  0.9856 

Bayes factors:
          Dayhoff   Neutral   Fitness
Dayhoff    1.0000    0.0191    0.0003
Neutral   52.4863    1.0000    0.0143
Fitness 3665.8286   69.8436    1.0000




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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0327  0.4700  0.4973 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.0695  0.0657
Neutral 14.3878  1.0000  0.9450
Fitness 15.2245  1.0582  1.0000


Posterior model probabilities (neuralnet):
Dayhoff Neutral Fitness 
 0.0001  0.0006  0.9993 

Bayes factors:
           Dayhoff    Neutral    Fitness
Dayhoff     1.0000     0.1255     0.0001
Neutral     7.9674     1.0000     0.0006
Fitness 13462.2327  1689.6620     1.0000




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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
  0.000   0.144   0.856 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.1682
Fitness     Inf  5.9444  1.0000





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.1133  0.8867 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.1278
Fitness     Inf  7.8235  1.0000





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0007  0.2853  0.7140 

Bayes factors:
          Dayhoff   Neutral   Fitness
Dayhoff    1.0000    0.0023    0.0009
Neutral  428.0000    1.0000    0.3996
Fitness 1071.0000    2.5023    1.0000


Posterior model probabilities (neuralnet):
Dayhoff Neutral Fitness 
 0.0000  0.0001  0.9998 

Bayes factors:
           Dayhoff    Neutral    Fitness
Dayhoff     1.0000     0.2780     0.0000
Neutral     3.5971     1.0000     0.0001
Fitness 29985.9729  8336.0907     1.0000




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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.0627  0.9373 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.0669
Fitness     Inf 14.9574  1.0000





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
   0.00    0.24    0.76 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.3158
Fitness     Inf  3.1667  1.0000





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0013  0.2827  0.7160 

Bayes factors:
         Dayhoff  Neutral  Fitness
Dayhoff   1.0000   0.0047   0.0019
Neutral 212.0000   1.0000   0.3948
Fitness 537.0000   2.5330   1.0000


Posterior model probabilities (neuralnet):
Dayhoff Neutral Fitness 
 0.0002  0.0001  0.9998 

Bayes factors:
           Dayhoff    Neutral    Fitness
Dayhoff     1.0000     2.2244     0.0002
Neutral     0.4496     1.0000     0.0001
Fitness  6222.6832 13841.7197     1.0000




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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.1753  0.8247 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.2126
Fitness     Inf  4.7034  1.0000





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

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

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





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0093  0.3873  0.6033 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.0241  0.0155
Neutral 41.5000  1.0000  0.6420
Fitness 64.6429  1.5577  1.0000


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

Bayes factors:
           Dayhoff    Neutral    Fitness
Dayhoff     1.0000     0.5050     0.0001
Neutral     1.9803     1.0000     0.0001
Fitness 15499.3543  7826.6739     1.0000




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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.1627  0.8373 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.1943
Fitness     Inf  5.1475  1.0000





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.2833  0.3647  0.3520 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.7770  0.8049
Neutral  1.2871  1.0000  1.0360
Fitness  1.2424  0.9653  1.0000


Posterior model probabilities (neuralnet):
Dayhoff Neutral Fitness 
 0.2946  0.0000  0.7054 

Bayes factors:
            Dayhoff     Neutral     Fitness
Dayhoff      1.0000  91759.8777      0.4177
Neutral      0.0000      1.0000      0.0000
Fitness      2.3942 219691.5583      1.0000




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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
  0.000   0.076   0.924 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.0823
Fitness     Inf 12.1579  1.0000





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

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

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.0204
Fitness     Inf 49.0000  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 (1500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
   0.00    0.43    0.57 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.7544
Fitness     Inf  1.3256  1.0000





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.1787  0.8213 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.2175
Fitness     Inf  4.5970  1.0000





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0107  0.2667  0.7227 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.0400  0.0148
Neutral 25.0000  1.0000  0.3690
Fitness 67.7500  2.7100  1.0000


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

Bayes factors:
           Dayhoff    Neutral    Fitness
Dayhoff     1.0000     2.2069     0.0000
Neutral     0.4531     1.0000     0.0000
Fitness 25238.2127 55698.8301     1.0000




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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0133  0.5133  0.4733 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.0260  0.0282
Neutral 38.5000  1.0000  1.0845
Fitness 35.5000  0.9221  1.0000


Posterior model probabilities (neuralnet):
Dayhoff Neutral Fitness 
 0.0001  0.0055  0.9945 

Bayes factors:
           Dayhoff    Neutral    Fitness
Dayhoff     1.0000     0.0113     0.0001
Neutral    88.4572     1.0000     0.0055
Fitness 16085.7876   181.8483     1.0000




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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0133  0.4973  0.4893 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.0268  0.0272
Neutral 37.3000  1.0000  1.0163
Fitness 36.7000  0.9839  1.0000


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

Bayes factors:
           Dayhoff    Neutral    Fitness
Dayhoff     1.0000     1.3848     0.0000
Neutral     0.7221     1.0000     0.0000
Fitness 39392.3778 54551.3228     1.0000




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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.1453  0.4380  0.4167 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.3318  0.3488
Neutral  3.0138  1.0000  1.0512
Fitness  2.8670  0.9513  1.0000


Posterior model probabilities (neuralnet):
Dayhoff Neutral Fitness 
 0.0049  0.0001  0.9950 

Bayes factors:
           Dayhoff    Neutral    Fitness
Dayhoff     1.0000    88.2982     0.0049
Neutral     0.0113     1.0000     0.0001
Fitness   202.3492 17867.0669     1.0000




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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.2740  0.4007  0.3253 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.6839  0.8422
Neutral  1.4623  1.0000  1.2316
Fitness  1.1873  0.8120  1.0000


Posterior model probabilities (neuralnet):
Dayhoff Neutral Fitness 
 0.2861  0.0018  0.7121 

Bayes factors:
         Dayhoff  Neutral  Fitness
Dayhoff   1.0000 156.4348   0.4018
Neutral   0.0064   1.0000   0.0026
Fitness   2.4887 389.3168   1.0000




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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
  0.000   0.092   0.908 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.1013
Fitness     Inf  9.8696  1.0000





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
  0.000   0.122   0.878 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.1390
Fitness     Inf  7.1967  1.0000





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.2727  0.4027  0.3247 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.6772  0.8398
Neutral  1.4768  1.0000  1.2402
Fitness  1.1907  0.8063  1.0000


Posterior model probabilities (neuralnet):
Dayhoff Neutral Fitness 
 0.1615  0.0002  0.8383 

Bayes factors:
          Dayhoff   Neutral   Fitness
Dayhoff    1.0000  994.9342    0.1926
Neutral    0.0010    1.0000    0.0002
Fitness    5.1914 5165.0612    1.0000




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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
  0.000   0.176   0.824 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.2136
Fitness     Inf  4.6818  1.0000





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.0353  0.9647 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.0366
Fitness     Inf 27.3019  1.0000





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.2567  0.4133  0.3300 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.6210  0.7778
Neutral  1.6104  1.0000  1.2525
Fitness  1.2857  0.7984  1.0000


Posterior model probabilities (neuralnet):
Dayhoff Neutral Fitness 
 0.1167  0.2227  0.6606 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.5240  0.1767
Neutral  1.9085  1.0000  0.3371
Fitness  5.6607  2.9661  1.0000




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

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

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





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
  0.000   0.138   0.862 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.1601
Fitness     Inf  6.2464  1.0000





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.2113  0.3840  0.4047 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.5503  0.5222
Neutral  1.8170  1.0000  0.9489
Fitness  1.9148  1.0538  1.0000


Posterior model probabilities (neuralnet):
Dayhoff Neutral Fitness 
 0.0001  0.0032  0.9967 

Bayes factors:
          Dayhoff   Neutral   Fitness
Dayhoff    1.0000    0.0442    0.0001
Neutral   22.6118    1.0000    0.0032
Fitness 7151.7062  316.2825    1.0000




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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0080  0.2933  0.6987 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.0273  0.0115
Neutral 36.6667  1.0000  0.4198
Fitness 87.3333  2.3818  1.0000


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

Bayes factors:
           Dayhoff    Neutral    Fitness
Dayhoff     1.0000     2.2032     0.0001
Neutral     0.4539     1.0000     0.0000
Fitness 14064.7718 30988.1618     1.0000




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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.2700  0.3987  0.3313 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.6773  0.8149
Neutral  1.4765  1.0000  1.2032
Fitness  1.2272  0.8311  1.0000


Posterior model probabilities (neuralnet):
Dayhoff Neutral Fitness 
 0.0548  0.0002  0.9450 

Bayes factors:
          Dayhoff   Neutral   Fitness
Dayhoff    1.0000  235.5196    0.0580
Neutral    0.0042    1.0000    0.0002
Fitness   17.2523 4063.2632    1.0000




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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0720  0.4127  0.5153 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.1745  0.1397
Neutral  5.7315  1.0000  0.8008
Fitness  7.1574  1.2488  1.0000


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

Bayes factors:
          Dayhoff   Neutral   Fitness
Dayhoff    1.0000    2.4401    0.0005
Neutral    0.4098    1.0000    0.0002
Fitness 1895.6683 4625.6216    1.0000




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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
  0.000   0.112   0.888 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.1261
Fitness     Inf  7.9286  1.0000





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.2713  0.3720  0.3567 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.7294  0.7607
Neutral  1.3710  1.0000  1.0430
Fitness  1.3145  0.9588  1.0000


Posterior model probabilities (neuralnet):
Dayhoff Neutral Fitness 
 0.0374  0.0000  0.9626 

Bayes factors:
             Dayhoff      Neutral      Fitness
Dayhoff       1.0000   82472.3150       0.0389
Neutral       0.0000       1.0000       0.0000
Fitness      25.7086 2120243.6860       1.0000




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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.2153  0.4067  0.3780 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.5295  0.5697
Neutral  1.8885  1.0000  1.0758
Fitness  1.7554  0.9295  1.0000


Posterior model probabilities (neuralnet):
Dayhoff Neutral Fitness 
 0.0215  0.0001  0.9784 

Bayes factors:
          Dayhoff   Neutral   Fitness
Dayhoff    1.0000  190.9630    0.0220
Neutral    0.0052    1.0000    0.0001
Fitness   45.5512 8698.5984    1.0000




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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.0287  0.9713 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.0295
Fitness     Inf 33.8837  1.0000





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.4293  0.5707 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.7523
Fitness     Inf  1.3292  1.0000





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

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

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.1765
Fitness     Inf  5.6667  1.0000





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.0207  0.9793 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.0211
Fitness     Inf 47.3871  1.0000





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0087  0.1033  0.8880 

Bayes factors:
         Dayhoff  Neutral  Fitness
Dayhoff   1.0000   0.0839   0.0098
Neutral  11.9231   1.0000   0.1164
Fitness 102.4615   8.5935   1.0000


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

Bayes factors:
            Dayhoff     Neutral     Fitness
Dayhoff      1.0000     18.3991      0.0001
Neutral      0.0544      1.0000      0.0000
Fitness   7232.2253 133066.5158      1.0000




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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.0247  0.9753 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.0253
Fitness     Inf 39.5405  1.0000





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.0547  0.9453 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.0578
Fitness     Inf 17.2927  1.0000





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.3307  0.6693 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.4940
Fitness     Inf  2.0242  1.0000





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0053  0.4173  0.5773 

Bayes factors:
         Dayhoff  Neutral  Fitness
Dayhoff   1.0000   0.0128   0.0092
Neutral  78.2500   1.0000   0.7229
Fitness 108.2500   1.3834   1.0000


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

Bayes factors:
           Dayhoff    Neutral    Fitness
Dayhoff     1.0000     1.8041     0.0000
Neutral     0.5543     1.0000     0.0000
Fitness 31474.9514 56782.5407     1.0000




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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.1713  0.8287 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.2068
Fitness     Inf  4.8366  1.0000





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.3967  0.6033 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.6575
Fitness     Inf  1.5210  1.0000





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.1853  0.8147 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.2275
Fitness     Inf  4.3957  1.0000





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.2127  0.7873 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.2701
Fitness     Inf  3.7022  1.0000





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.2893  0.3447  0.3660 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.8395  0.7905
Neutral  1.1912  1.0000  0.9417
Fitness  1.2650  1.0619  1.0000


Posterior model probabilities (neuralnet):
Dayhoff Neutral Fitness 
 0.3220  0.0000  0.6779 

Bayes factors:
           Dayhoff    Neutral    Fitness
Dayhoff     1.0000  9086.5775     0.4750
Neutral     0.0001     1.0000     0.0001
Fitness     2.1052 19128.8202     1.0000




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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.1527  0.8473 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.1802
Fitness     Inf  5.5502  1.0000





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.1167  0.3360  0.5473 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.3472  0.2132
Neutral  2.8800  1.0000  0.6139
Fitness  4.6914  1.6290  1.0000


Posterior model probabilities (neuralnet):
Dayhoff Neutral Fitness 
 0.0008  0.0000  0.9992 

Bayes factors:
           Dayhoff    Neutral    Fitness
Dayhoff     1.0000    16.3364     0.0008
Neutral     0.0612     1.0000     0.0000
Fitness  1251.3085 20441.8858     1.0000




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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.1867  0.4413  0.3720 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.4230  0.5018
Neutral  2.3643  1.0000  1.1864
Fitness  1.9929  0.8429  1.0000


Posterior model probabilities (neuralnet):
Dayhoff Neutral Fitness 
 0.0054  0.0005  0.9941 

Bayes factors:
          Dayhoff   Neutral   Fitness
Dayhoff    1.0000   11.0254    0.0054
Neutral    0.0907    1.0000    0.0005
Fitness  185.2886 2042.8834    1.0000




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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.1253  0.8747 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.1433
Fitness     Inf  6.9787  1.0000





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.0713  0.9287 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.0768
Fitness     Inf 13.0187  1.0000





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
  0.000   0.362   0.638 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.5674
Fitness     Inf  1.7624  1.0000





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.2680  0.4087  0.3233 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.6558  0.8289
Neutral  1.5249  1.0000  1.2639
Fitness  1.2065  0.7912  1.0000


Posterior model probabilities (neuralnet):
Dayhoff Neutral Fitness 
 0.4194  0.0102  0.5704 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000 41.0119  0.7352
Neutral  0.0244  1.0000  0.0179
Fitness  1.3603 55.7868  1.0000




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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.1153  0.8847 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.1304
Fitness     Inf  7.6705  1.0000





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.0753  0.9247 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.0815
Fitness     Inf 12.2743  1.0000





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0033  0.4433  0.5533 

Bayes factors:
         Dayhoff  Neutral  Fitness
Dayhoff   1.0000   0.0075   0.0060
Neutral 133.0000   1.0000   0.8012
Fitness 166.0000   1.2481   1.0000


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

Bayes factors:
           Dayhoff    Neutral    Fitness
Dayhoff     1.0000     2.2861     0.0000
Neutral     0.4374     1.0000     0.0000
Fitness 38428.5340 87849.9943     1.0000




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

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

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





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

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

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.0453
Fitness     Inf 22.0769  1.0000





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.1073  0.4587  0.4340 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.2340  0.2473
Neutral  4.2733  1.0000  1.0568
Fitness  4.0435  0.9462  1.0000


Posterior model probabilities (neuralnet):
Dayhoff Neutral Fitness 
 0.0007  0.0001  0.9993 

Bayes factors:
           Dayhoff    Neutral    Fitness
Dayhoff     1.0000     8.4833     0.0007
Neutral     0.1179     1.0000     0.0001
Fitness  1522.8744 12919.0133     1.0000




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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0267  0.3640  0.6093 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.0733  0.0438
Neutral 13.6500  1.0000  0.5974
Fitness 22.8500  1.6740  1.0000


Posterior model probabilities (neuralnet):
Dayhoff Neutral Fitness 
 0.0002  0.0000  0.9997 

Bayes factors:
           Dayhoff    Neutral    Fitness
Dayhoff     1.0000     8.9778     0.0002
Neutral     0.1114     1.0000     0.0000
Fitness  4337.2991 38939.5614     1.0000




