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      93       1       6
Neutral       0      97       3
Fitness       1       2      97


Mean model posterior probabilities (neuralnet)

$tol0.01
        Dayhoff Neutral Fitness
Dayhoff  0.9264  0.0062  0.0674
Neutral  0.0032  0.9467  0.0502
Fitness  0.0186  0.0469  0.9345




Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.0157  0.9843 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.0159
Fitness     Inf 62.8298  1.0000





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.1600  0.4297  0.4103 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.3724  0.3899
Neutral  2.6854  1.0000  1.0471
Fitness  2.5646  0.9550  1.0000


Posterior model probabilities (neuralnet):
Dayhoff Neutral Fitness 
 0.0277  0.0000  0.9723 

Bayes factors:
           Dayhoff    Neutral    Fitness
Dayhoff     1.0000  2491.2656     0.0284
Neutral     0.0004     1.0000     0.0000
Fitness    35.1651 87605.5619     1.0000




Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

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

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.0260
Fitness     Inf 38.4737  1.0000





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
  0.000   0.037   0.963 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.0384
Fitness     Inf 26.0270  1.0000





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
  0.000   0.116   0.884 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.1312
Fitness     Inf  7.6207  1.0000





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
  0.000   0.003   0.997 

Bayes factors:
         Dayhoff  Neutral  Fitness
Dayhoff            0.0000   0.0000
Neutral      Inf   1.0000   0.0030
Fitness      Inf 332.3333   1.0000





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.0117  0.9883 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.0118
Fitness     Inf 84.7143  1.0000





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.0003  0.9997 

Bayes factors:
          Dayhoff   Neutral   Fitness
Dayhoff              0.0000    0.0000
Neutral       Inf    1.0000    0.0003
Fitness       Inf 2999.0000    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 (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0017  0.0000  0.9983 

Bayes factors:
         Dayhoff  Neutral  Fitness
Dayhoff   1.0000      Inf   0.0017
Neutral   0.0000            0.0000
Fitness 599.0000      Inf   1.0000





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.0637  0.9363 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.0680
Fitness     Inf 14.7068  1.0000





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.2767  0.3650  0.3583 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.7580  0.7721
Neutral  1.3193  1.0000  1.0186
Fitness  1.2952  0.9817  1.0000


Posterior model probabilities (neuralnet):
Dayhoff Neutral Fitness 
 0.1444  0.0000  0.8556 

Bayes factors:
             Dayhoff      Neutral      Fitness
Dayhoff       1.0000  219738.5166       0.1688
Neutral       0.0000       1.0000       0.0000
Fitness       5.9248 1301904.8626       1.0000




Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.0543  0.9457 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.0575
Fitness     Inf 17.4049  1.0000





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

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

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





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.0017  0.9983 

Bayes factors:
         Dayhoff  Neutral  Fitness
Dayhoff            0.0000   0.0000
Neutral      Inf   1.0000   0.0017
Fitness      Inf 599.0000   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 (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.0503  0.9497 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.0530
Fitness     Inf 18.8675  1.0000





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
   0.00    0.08    0.92 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff           0.000   0.000
Neutral     Inf   1.000   0.087
Fitness     Inf  11.500   1.000





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0067  0.3237  0.6697 

Bayes factors:
         Dayhoff  Neutral  Fitness
Dayhoff   1.0000   0.0206   0.0100
Neutral  48.5500   1.0000   0.4833
Fitness 100.4500   2.0690   1.0000


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

Bayes factors:
           Dayhoff    Neutral    Fitness
Dayhoff     1.0000     3.0514     0.0001
Neutral     0.3277     1.0000     0.0000
Fitness  7747.0777 23639.8039     1.0000




Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.2207  0.3513  0.4280 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.6281  0.5156
Neutral  1.5921  1.0000  0.8209
Fitness  1.9396  1.2182  1.0000


Posterior model probabilities (neuralnet):
Dayhoff Neutral Fitness 
 0.0621  0.0000  0.9379 

Bayes factors:
             Dayhoff      Neutral      Fitness
Dayhoff       1.0000   67220.7903       0.0663
Neutral       0.0000       1.0000       0.0000
Fitness      15.0910 1014430.9232       1.0000




Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0003  0.1567  0.8430 

Bayes factors:
          Dayhoff   Neutral   Fitness
Dayhoff    1.0000    0.0021    0.0004
Neutral  470.0000    1.0000    0.1858
Fitness 2529.0000    5.3809    1.0000


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

Bayes factors:
            Dayhoff     Neutral     Fitness
Dayhoff      1.0000      2.9591      0.0000
Neutral      0.3379      1.0000      0.0000
Fitness  54222.2851 160450.6779      1.0000




Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
  0.007   0.423   0.570 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.0165  0.0123
Neutral 60.4286  1.0000  0.7421
Fitness 81.4286  1.3475  1.0000


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

Bayes factors:
           Dayhoff    Neutral    Fitness
Dayhoff     1.0000     0.6029     0.0000
Neutral     1.6587     1.0000     0.0000
Fitness 59065.2280 35610.3538     1.0000




Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.0017  0.9983 

Bayes factors:
         Dayhoff  Neutral  Fitness
Dayhoff            0.0000   0.0000
Neutral      Inf   1.0000   0.0017
Fitness      Inf 599.0000   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 (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0367  0.4460  0.5173 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.0822  0.0709
Neutral 12.1636  1.0000  0.8621
Fitness 14.1091  1.1599  1.0000


Posterior model probabilities (neuralnet):
Dayhoff Neutral Fitness 
 0.0001  0.0001  0.9997 

Bayes factors:
          Dayhoff   Neutral   Fitness
Dayhoff    1.0000    0.7262    0.0001
Neutral    1.3770    1.0000    0.0001
Fitness 9424.9555 6844.5966    1.0000




Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.0003  0.9997 

Bayes factors:
          Dayhoff   Neutral   Fitness
Dayhoff              0.0000    0.0000
Neutral       Inf    1.0000    0.0003
Fitness       Inf 2999.0000    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 (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.2283  0.4150  0.3567 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.5502  0.6402
Neutral  1.8175  1.0000  1.1636
Fitness  1.5620  0.8594  1.0000


Posterior model probabilities (neuralnet):
Dayhoff Neutral Fitness 
 0.1935  0.4385  0.3680 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.4412  0.5257
Neutral  2.2665  1.0000  1.1915
Fitness  1.9022  0.8393  1.0000




Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.0023  0.9977 

Bayes factors:
         Dayhoff  Neutral  Fitness
Dayhoff            0.0000   0.0000
Neutral      Inf   1.0000   0.0023
Fitness      Inf 427.5714   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 (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

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

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





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.0097  0.9903 

Bayes factors:
         Dayhoff  Neutral  Fitness
Dayhoff            0.0000   0.0000
Neutral      Inf   1.0000   0.0098
Fitness      Inf 102.4483   1.0000





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.0883  0.9117 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.0969
Fitness     Inf 10.3208  1.0000





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

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

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





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0487  0.5460  0.4053 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.0891  0.1201
Neutral 11.2192  1.0000  1.3470
Fitness  8.3288  0.7424  1.0000


Posterior model probabilities (neuralnet):
Dayhoff Neutral Fitness 
 0.0023  0.0010  0.9967 

Bayes factors:
          Dayhoff   Neutral   Fitness
Dayhoff    1.0000    2.3830    0.0023
Neutral    0.4196    1.0000    0.0010
Fitness  429.4206 1023.3157    1.0000




Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.2550  0.3427  0.4023 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.7442  0.6338
Neutral  1.3438  1.0000  0.8517
Fitness  1.5778  1.1741  1.0000


Posterior model probabilities (neuralnet):
Dayhoff Neutral Fitness 
 0.0563  0.0000  0.9437 

Bayes factors:
           Dayhoff    Neutral    Fitness
Dayhoff     1.0000  2312.7056     0.0597
Neutral     0.0004     1.0000     0.0000
Fitness    16.7642 38770.6731     1.0000




Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.0223  0.9777 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.0228
Fitness     Inf 43.7761  1.0000





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.2563  0.3880  0.3557 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.6607  0.7207
Neutral  1.5137  1.0000  1.0909
Fitness  1.3875  0.9167  1.0000


Posterior model probabilities (neuralnet):
Dayhoff Neutral Fitness 
 0.4795  0.0028  0.5176 

Bayes factors:
         Dayhoff  Neutral  Fitness
Dayhoff   1.0000 168.6368   0.9265
Neutral   0.0059   1.0000   0.0055
Fitness   1.0794 182.0206   1.0000




Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.2527  0.3947  0.3527 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.6402  0.7164
Neutral  1.5620  1.0000  1.1191
Fitness  1.3958  0.8936  1.0000


Posterior model probabilities (neuralnet):
Dayhoff Neutral Fitness 
 0.3229  0.0467  0.6304 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  6.9115  0.5122
Neutral  0.1447  1.0000  0.0741
Fitness  1.9522 13.4927  1.0000




Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.0443  0.9557 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.0464
Fitness     Inf 21.5564  1.0000





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
  0.000   0.296   0.704 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.4205
Fitness     Inf  2.3784  1.0000





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0043  0.3483  0.6473 

Bayes factors:
         Dayhoff  Neutral  Fitness
Dayhoff   1.0000   0.0124   0.0067
Neutral  80.3846   1.0000   0.5381
Fitness 149.3846   1.8584   1.0000


Posterior model probabilities (neuralnet):
Dayhoff Neutral Fitness 
 0.0001  0.0002  0.9997 

Bayes factors:
           Dayhoff    Neutral    Fitness
Dayhoff     1.0000     0.2675     0.0001
Neutral     3.7380     1.0000     0.0002
Fitness 18561.3939  4965.5541     1.0000




Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.0147  0.9853 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.0149
Fitness     Inf 67.1818  1.0000





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

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

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





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.0917  0.9083 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.1009
Fitness     Inf  9.9091  1.0000





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

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

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





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.0113  0.9887 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.0115
Fitness     Inf 87.2353  1.0000





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.0513  0.9487 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.0541
Fitness     Inf 18.4805  1.0000





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.0017  0.9983 

Bayes factors:
         Dayhoff  Neutral  Fitness
Dayhoff            0.0000   0.0000
Neutral      Inf   1.0000   0.0017
Fitness      Inf 599.0000   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 (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

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

Bayes factors:
         Dayhoff  Neutral  Fitness
Dayhoff            0.0000   0.0000
Neutral      Inf   1.0000   0.0033
Fitness      Inf 299.0000   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 (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0010  0.1047  0.8943 

Bayes factors:
         Dayhoff  Neutral  Fitness
Dayhoff   1.0000   0.0096   0.0011
Neutral 104.6667   1.0000   0.1170
Fitness 894.3333   8.5446   1.0000


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

Bayes factors:
           Dayhoff    Neutral    Fitness
Dayhoff     1.0000     1.8107     0.0001
Neutral     0.5523     1.0000     0.0001
Fitness  9143.8655 16556.6372     1.0000




Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

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

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.0653
Fitness     Inf 15.3043  1.0000





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.3617  0.2037  0.4347 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  1.7758  0.8321
Neutral  0.5631  1.0000  0.4686
Fitness  1.2018  2.1342  1.0000


Posterior model probabilities (neuralnet):
Dayhoff Neutral Fitness 
 0.3135  0.0000  0.6865 

Bayes factors:
             Dayhoff      Neutral      Fitness
Dayhoff 1.000000e+00 2.776423e+07 4.567000e-01
Neutral 0.000000e+00 1.000000e+00 0.000000e+00
Fitness 2.189500e+00 6.078943e+07 1.000000e+00




Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
  0.000   0.001   0.999 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff           0.000   0.000
Neutral     Inf   1.000   0.001
Fitness     Inf 999.000   1.000





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
  0.000   0.001   0.999 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff           0.000   0.000
Neutral     Inf   1.000   0.001
Fitness     Inf 999.000   1.000





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.2013  0.7987 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.2521
Fitness     Inf  3.9669  1.0000





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (3000 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 (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0010  0.0387  0.9603 

Bayes factors:
         Dayhoff  Neutral  Fitness
Dayhoff   1.0000   0.0259   0.0010
Neutral  38.6667   1.0000   0.0403
Fitness 960.3333  24.8362   1.0000


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

Bayes factors:
            Dayhoff     Neutral     Fitness
Dayhoff      1.0000      2.3025      0.0000
Neutral      0.4343      1.0000      0.0000
Fitness 222848.3336 513107.2600      1.0000




Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
  0.002   0.464   0.534 

Bayes factors:
         Dayhoff  Neutral  Fitness
Dayhoff   1.0000   0.0043   0.0037
Neutral 232.0000   1.0000   0.8689
Fitness 267.0000   1.1509   1.0000


Posterior model probabilities (neuralnet):
Dayhoff Neutral Fitness 
 0.0002  0.0396  0.9602 

Bayes factors:
          Dayhoff   Neutral   Fitness
Dayhoff    1.0000    0.0047    0.0002
Neutral  210.5964    1.0000    0.0412
Fitness 5111.2126   24.2702    1.0000




Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0027  0.3933  0.6040 

Bayes factors:
         Dayhoff  Neutral  Fitness
Dayhoff   1.0000   0.0068   0.0044
Neutral 147.5000   1.0000   0.6512
Fitness 226.5000   1.5356   1.0000


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

Bayes factors:
           Dayhoff    Neutral    Fitness
Dayhoff     1.0000    51.4546     0.0008
Neutral     0.0194     1.0000     0.0000
Fitness  1247.5289 64191.0456     1.0000




Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0757  0.3030  0.6213 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.2497  0.1218
Neutral  4.0044  1.0000  0.4877
Fitness  8.2115  2.0506  1.0000


Posterior model probabilities (neuralnet):
Dayhoff Neutral Fitness 
 0.0103  0.0000  0.9896 

Bayes factors:
           Dayhoff    Neutral    Fitness
Dayhoff     1.0000   217.5064     0.0105
Neutral     0.0046     1.0000     0.0000
Fitness    95.6840 20811.8917     1.0000




Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
  0.260   0.399   0.341 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.6516  0.7625
Neutral  1.5346  1.0000  1.1701
Fitness  1.3115  0.8546  1.0000


Posterior model probabilities (neuralnet):
Dayhoff Neutral Fitness 
 0.1694  0.0000  0.8306 

Bayes factors:
            Dayhoff     Neutral     Fitness
Dayhoff      1.0000  86585.8970      0.2040
Neutral      0.0000      1.0000      0.0000
Fitness      4.9022 424463.0178      1.0000




Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
  0.000   0.007   0.993 

Bayes factors:
         Dayhoff  Neutral  Fitness
Dayhoff            0.0000   0.0000
Neutral      Inf   1.0000   0.0070
Fitness      Inf 141.8571   1.0000





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
  0.000   0.014   0.986 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.0142
Fitness     Inf 70.4286  1.0000





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.2597  0.3983  0.3420 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.6519  0.7593
Neutral  1.5340  1.0000  1.1647
Fitness  1.3171  0.8586  1.0000


Posterior model probabilities (neuralnet):
Dayhoff Neutral Fitness 
 0.1133  0.0393  0.8475 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  2.8853  0.1337
Neutral  0.3466  1.0000  0.0463
Fitness  7.4821 21.5880  1.0000




Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

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

Bayes factors:
         Dayhoff  Neutral  Fitness
Dayhoff            0.0000   0.0000
Neutral      Inf   1.0000   0.0013
Fitness      Inf 749.0000   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 (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
  0.000   0.009   0.991 

Bayes factors:
         Dayhoff  Neutral  Fitness
Dayhoff            0.0000   0.0000
Neutral      Inf   1.0000   0.0091
Fitness      Inf 110.1111   1.0000





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.2283  0.4147  0.3570 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.5506  0.6396
Neutral  1.8161  1.0000  1.1615
Fitness  1.5635  0.8609  1.0000


Posterior model probabilities (neuralnet):
Dayhoff Neutral Fitness 
 0.1917  0.2910  0.5172 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.6587  0.3707
Neutral  1.5181  1.0000  0.5627
Fitness  2.6980  1.7772  1.0000




Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.0003  0.9997 

Bayes factors:
          Dayhoff   Neutral   Fitness
Dayhoff              0.0000    0.0000
Neutral       Inf    1.0000    0.0003
Fitness       Inf 2999.0000    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 (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.0517  0.9483 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.0545
Fitness     Inf 18.3548  1.0000





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.1243  0.2907  0.5850 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.4278  0.2125
Neutral  2.3378  1.0000  0.4969
Fitness  4.7051  2.0126  1.0000


Posterior model probabilities (neuralnet):
Dayhoff Neutral Fitness 
 0.0238  0.0285  0.9477 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.8343  0.0251
Neutral  1.1986  1.0000  0.0301
Fitness 39.8607 33.2573  1.0000




Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0007  0.0517  0.9477 

Bayes factors:
          Dayhoff   Neutral   Fitness
Dayhoff    1.0000    0.0129    0.0007
Neutral   77.5000    1.0000    0.0545
Fitness 1421.5000   18.3419    1.0000


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

Bayes factors:
            Dayhoff     Neutral     Fitness
Dayhoff      1.0000      3.7843      0.0000
Neutral      0.2642      1.0000      0.0000
Fitness  47840.6164 181044.6355      1.0000




Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.2237  0.4340  0.3423 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.5154  0.6534
Neutral  1.9404  1.0000  1.2678
Fitness  1.5306  0.7888  1.0000


Posterior model probabilities (neuralnet):
Dayhoff Neutral Fitness 
 0.0596  0.0000  0.9404 

Bayes factors:
           Dayhoff    Neutral    Fitness
Dayhoff     1.0000  3849.3166     0.0634
Neutral     0.0003     1.0000     0.0000
Fitness    15.7789 60737.9992     1.0000




Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
  0.029   0.190   0.781 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.1526  0.0371
Neutral  6.5517  1.0000  0.2433
Fitness 26.9310  4.1105  1.0000


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

Bayes factors:
            Dayhoff     Neutral     Fitness
Dayhoff      1.0000      0.1880      0.0000
Neutral      5.3203      1.0000      0.0000
Fitness 175175.8482  32926.1796      1.0000




Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
  0.000   0.019   0.981 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.0194
Fitness     Inf 51.6316  1.0000





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
  0.260   0.261   0.479 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.9962  0.5428
Neutral  1.0038  1.0000  0.5449
Fitness  1.8423  1.8352  1.0000


Posterior model probabilities (neuralnet):
Dayhoff Neutral Fitness 
 0.0559  0.0000  0.9441 

Bayes factors:
           Dayhoff    Neutral    Fitness
Dayhoff     1.0000  4719.0638     0.0592
Neutral     0.0002     1.0000     0.0000
Fitness    16.8868 79690.1017     1.0000




Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.1280  0.4197  0.4523 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.3050  0.2830
Neutral  3.2786  1.0000  0.9278
Fitness  3.5339  1.0778  1.0000


Posterior model probabilities (neuralnet):
Dayhoff Neutral Fitness 
 0.0377  0.0001  0.9622 

Bayes factors:
          Dayhoff   Neutral   Fitness
Dayhoff    1.0000  272.7560    0.0391
Neutral    0.0037    1.0000    0.0001
Fitness   25.5498 6968.8523    1.0000




Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

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

Bayes factors:
         Dayhoff  Neutral  Fitness
Dayhoff            0.0000   0.0000
Neutral      Inf   1.0000   0.0013
Fitness      Inf 749.0000   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 (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.1707  0.8293 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.2058
Fitness     Inf  4.8594  1.0000





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.0587  0.9413 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.0623
Fitness     Inf 16.0455  1.0000





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

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

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





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0010  0.0017  0.9973 

Bayes factors:
         Dayhoff  Neutral  Fitness
Dayhoff   1.0000   0.6000   0.0010
Neutral   1.6667   1.0000   0.0017
Fitness 997.3333 598.4000   1.0000


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

Bayes factors:
           Dayhoff    Neutral    Fitness
Dayhoff     1.0000     3.7973     0.0001
Neutral     0.2633     1.0000     0.0000
Fitness 14607.7903 55469.4631     1.0000




Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
  0.000   0.001   0.999 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff           0.000   0.000
Neutral     Inf   1.000   0.001
Fitness     Inf 999.000   1.000





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

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

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.0101
Fitness     Inf 99.0000  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 (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.0393  0.9607 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.0409
Fitness     Inf 24.4237  1.0000





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
  0.000   0.242   0.758 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.3193
Fitness     Inf  3.1322  1.0000





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (3000 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 (3000 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 (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

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

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





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
  0.000   0.065   0.935 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.0695
Fitness     Inf 14.3846  1.0000





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.4013  0.1470  0.4517 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  2.7302  0.8886
Neutral  0.3663  1.0000  0.3255
Fitness  1.1254  3.0726  1.0000


Posterior model probabilities (neuralnet):
Dayhoff Neutral Fitness 
 0.3438  0.0000  0.6562 

Bayes factors:
           Dayhoff    Neutral    Fitness
Dayhoff     1.0000 12701.7248     0.5240
Neutral     0.0001     1.0000     0.0000
Fitness     1.9084 24239.9592     1.0000




Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.0057  0.9943 

Bayes factors:
         Dayhoff  Neutral  Fitness
Dayhoff            0.0000   0.0000
Neutral      Inf   1.0000   0.0057
Fitness      Inf 175.4706   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 (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
  0.067   0.107   0.826 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.6262  0.0811
Neutral  1.5970  1.0000  0.1295
Fitness 12.3284  7.7196  1.0000


Posterior model probabilities (neuralnet):
Dayhoff Neutral Fitness 
 0.0056  0.0053  0.9891 

Bayes factors:
         Dayhoff  Neutral  Fitness
Dayhoff   1.0000   1.0584   0.0057
Neutral   0.9448   1.0000   0.0054
Fitness 176.1478 186.4366   1.0000




Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0797  0.4733  0.4470 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.1683  0.1782
Neutral  5.9414  1.0000  1.0589
Fitness  5.6109  0.9444  1.0000


Posterior model probabilities (neuralnet):
Dayhoff Neutral Fitness 
 0.0170  0.0921  0.8909 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.1847  0.0191
Neutral  5.4145  1.0000  0.1034
Fitness 52.3811  9.6742  1.0000




Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.0663  0.9337 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.0710
Fitness     Inf 14.0754  1.0000





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

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

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





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.0793  0.9207 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.0862
Fitness     Inf 11.6050  1.0000





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.2470  0.3973  0.3557 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.6216  0.6945
Neutral  1.6086  1.0000  1.1172
Fitness  1.4399  0.8951  1.0000


Posterior model probabilities (neuralnet):
Dayhoff Neutral Fitness 
 0.3829  0.0516  0.5655 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  7.4283  0.6771
Neutral  0.1346  1.0000  0.0912
Fitness  1.4768 10.9703  1.0000




Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

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

Bayes factors:
         Dayhoff  Neutral  Fitness
Dayhoff            0.0000   0.0000
Neutral      Inf   1.0000   0.0027
Fitness      Inf 374.0000   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 (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.0097  0.9903 

Bayes factors:
         Dayhoff  Neutral  Fitness
Dayhoff            0.0000   0.0000
Neutral      Inf   1.0000   0.0098
Fitness      Inf 102.4483   1.0000





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0007  0.2233  0.7760 

Bayes factors:
          Dayhoff   Neutral   Fitness
Dayhoff    1.0000    0.0030    0.0009
Neutral  335.0000    1.0000    0.2878
Fitness 1164.0000    3.4746    1.0000


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

Bayes factors:
            Dayhoff     Neutral     Fitness
Dayhoff      1.0000      2.6472      0.0000
Neutral      0.3778      1.0000      0.0000
Fitness  53804.7299 142432.8993      1.0000




Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.0077  0.9923 

Bayes factors:
         Dayhoff  Neutral  Fitness
Dayhoff            0.0000   0.0000
Neutral      Inf   1.0000   0.0077
Fitness      Inf 129.4348   1.0000





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.0063  0.9937 

Bayes factors:
         Dayhoff  Neutral  Fitness
Dayhoff            0.0000   0.0000
Neutral      Inf   1.0000   0.0064
Fitness      Inf 156.8947   1.0000





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0323  0.3580  0.6097 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.0903  0.0530
Neutral 11.0722  1.0000  0.5872
Fitness 18.8557  1.7030  1.0000


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

Bayes factors:
           Dayhoff    Neutral    Fitness
Dayhoff     1.0000     5.7570     0.0001
Neutral     0.1737     1.0000     0.0000
Fitness 13104.0821 75440.5398     1.0000




Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0097  0.0470  0.9433 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.2057  0.0102
Neutral  4.8621  1.0000  0.0498
Fitness 97.5862 20.0709  1.0000


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

Bayes factors:
            Dayhoff     Neutral     Fitness
Dayhoff      1.0000     20.2359      0.0001
Neutral      0.0494      1.0000      0.0000
Fitness  10131.8983 205027.9366      1.0000




