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      97       0       3
Neutral       0      96       4
Fitness       2       1      97


Mean model posterior probabilities (neuralnet)

$tol0.05
        Dayhoff Neutral Fitness
Dayhoff  0.9716  0.0001  0.0283
Neutral  0.0014  0.8703  0.1284
Fitness  0.0312  0.1148  0.8540




Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (7500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.0799  0.9201 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.0868
Fitness     Inf 11.5209  1.0000





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (7500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.2448  0.4016  0.3536 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.6096  0.6923
Neutral  1.6405  1.0000  1.1357
Fitness  1.4444  0.8805  1.0000


Posterior model probabilities (neuralnet):
Dayhoff Neutral Fitness 
 0.0289  0.0001  0.9710 

Bayes factors:
           Dayhoff    Neutral    Fitness
Dayhoff     1.0000   355.3764     0.0297
Neutral     0.0028     1.0000     0.0001
Fitness    33.6262 11949.9539     1.0000




Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (7500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.0872  0.9128 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.0955
Fitness     Inf 10.4679  1.0000





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (7500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.1203  0.8797 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.1367
Fitness     Inf  7.3149  1.0000





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (7500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
  0.000   0.368   0.632 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.5823
Fitness     Inf  1.7174  1.0000





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (7500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.1537  0.8463 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.1817
Fitness     Inf  5.5048  1.0000





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (7500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.0915  0.9085 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.1007
Fitness     Inf  9.9329  1.0000





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (7500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.0355  0.9645 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.0368
Fitness     Inf 27.1955  1.0000





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (7500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0127  0.0828  0.9045 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.1530  0.0140
Neutral  6.5368  1.0000  0.0915
Fitness 71.4105 10.9243  1.0000


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

Bayes factors:
            Dayhoff     Neutral     Fitness
Dayhoff      1.0000     31.2819      0.0000
Neutral      0.0320      1.0000      0.0000
Fitness  27460.6658 859021.5673      1.0000




Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (7500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0011  0.3264  0.6725 

Bayes factors:
         Dayhoff  Neutral  Fitness
Dayhoff   1.0000   0.0033   0.0016
Neutral 306.0000   1.0000   0.4853
Fitness 630.5000   2.0605   1.0000


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

Bayes factors:
            Dayhoff     Neutral     Fitness
Dayhoff      1.0000      0.9026      0.0000
Neutral      1.1079      1.0000      0.0000
Fitness 144250.0697 130205.4850      1.0000




Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (7500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.2647  0.3940  0.3413 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.6717  0.7754
Neutral  1.4887  1.0000  1.1543
Fitness  1.2897  0.8663  1.0000


Posterior model probabilities (neuralnet):
Dayhoff Neutral Fitness 
 0.1307  0.0001  0.8692 

Bayes factors:
          Dayhoff   Neutral   Fitness
Dayhoff    1.0000 1021.0458    0.1504
Neutral    0.0010    1.0000    0.0001
Fitness    6.6511 6791.0539    1.0000




Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (7500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.2303  0.7697 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.2992
Fitness     Inf  3.3428  1.0000





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (7500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.0855  0.9145 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.0935
Fitness     Inf 10.7005  1.0000





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (7500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.0137  0.9863 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.0139
Fitness     Inf 71.8155  1.0000





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (7500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.1944  0.8056 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.2413
Fitness     Inf  4.1440  1.0000





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (7500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.3515  0.6485 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.5419
Fitness     Inf  1.8452  1.0000





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (7500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0245  0.4801  0.4953 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.0511  0.0495
Neutral 19.5707  1.0000  0.9693
Fitness 20.1902  1.0317  1.0000


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

Bayes factors:
           Dayhoff    Neutral    Fitness
Dayhoff     1.0000     1.9546     0.0001
Neutral     0.5116     1.0000     0.0000
Fitness 18157.6980 35491.4547     1.0000




Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (7500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.2517  0.3877  0.3605 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.6492  0.6982
Neutral  1.5403  1.0000  1.0754
Fitness  1.4322  0.9298  1.0000


Posterior model probabilities (neuralnet):
Dayhoff Neutral Fitness 
 0.0782  0.0000  0.9218 

Bayes factors:
             Dayhoff      Neutral      Fitness
Dayhoff 1.000000e+00 2.121362e+06 8.480000e-02
Neutral 0.000000e+00 1.000000e+00 0.000000e+00
Fitness 1.179420e+01 2.501976e+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 (7500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0124  0.4195  0.5681 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.0296  0.0218
Neutral 33.8280  1.0000  0.7383
Fitness 45.8172  1.3544  1.0000


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

Bayes factors:
            Dayhoff     Neutral     Fitness
Dayhoff      1.0000      2.6728      0.0000
Neutral      0.3741      1.0000      0.0000
Fitness  81854.3496 218778.1500      1.0000




Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (7500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0572  0.4841  0.4587 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.1181  0.1247
Neutral  8.4639  1.0000  1.0555
Fitness  8.0186  0.9474  1.0000


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

Bayes factors:
           Dayhoff    Neutral    Fitness
Dayhoff     1.0000     2.5011     0.0001
Neutral     0.3998     1.0000     0.0000
Fitness  8817.2360 22052.5895     1.0000




Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (7500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

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

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.0563
Fitness     Inf 17.7500  1.0000





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (7500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.1111  0.4664  0.4225 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.2381  0.2629
Neutral  4.1993  1.0000  1.1038
Fitness  3.8043  0.9059  1.0000


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

Bayes factors:
          Dayhoff   Neutral   Fitness
Dayhoff    1.0000    0.7771    0.0002
Neutral    1.2869    1.0000    0.0003
Fitness 4710.9409 3660.6672    1.0000




Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (7500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.0313  0.9687 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.0323
Fitness     Inf 30.9149  1.0000





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (7500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.2535  0.3991  0.3475 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.6351  0.7295
Neutral  1.5744  1.0000  1.1485
Fitness  1.3709  0.8707  1.0000


Posterior model probabilities (neuralnet):
Dayhoff Neutral Fitness 
 0.2113  0.4226  0.3662 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.4999  0.5769
Neutral  2.0002  1.0000  1.1540
Fitness  1.7333  0.8666  1.0000




Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (7500 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 (7500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.0232  0.9768 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.0238
Fitness     Inf 42.1034  1.0000





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (7500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0005  0.0676  0.9319 

Bayes factors:
          Dayhoff   Neutral   Fitness
Dayhoff    1.0000    0.0079    0.0006
Neutral  126.7500    1.0000    0.0725
Fitness 1747.2500   13.7850    1.0000


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

Bayes factors:
           Dayhoff    Neutral    Fitness
Dayhoff     1.0000     1.3897     0.0000
Neutral     0.7196     1.0000     0.0000
Fitness 55899.6728 77685.2610     1.0000




Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (7500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.3932  0.6068 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.6480
Fitness     Inf  1.5432  1.0000





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (7500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0023  0.3592  0.6385 

Bayes factors:
         Dayhoff  Neutral  Fitness
Dayhoff   1.0000   0.0063   0.0035
Neutral 158.4706   1.0000   0.5625
Fitness 281.7059   1.7777   1.0000


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

Bayes factors:
            Dayhoff     Neutral     Fitness
Dayhoff      1.0000      1.6936      0.0000
Neutral      0.5905      1.0000      0.0000
Fitness 293652.3206 497327.0402      1.0000




Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (7500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.1769  0.4432  0.3799 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.3992  0.4658
Neutral  2.5049  1.0000  1.1667
Fitness  2.1469  0.8571  1.0000


Posterior model probabilities (neuralnet):
Dayhoff Neutral Fitness 
 0.0029  0.0009  0.9963 

Bayes factors:
          Dayhoff   Neutral   Fitness
Dayhoff    1.0000    3.2885    0.0029
Neutral    0.3041    1.0000    0.0009
Fitness  349.4535 1149.1926    1.0000




Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (7500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.2497  0.3705  0.3797 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.6740  0.6577
Neutral  1.4837  1.0000  0.9758
Fitness  1.5206  1.0248  1.0000


Posterior model probabilities (neuralnet):
Dayhoff Neutral Fitness 
 0.1106  0.0000  0.8894 

Bayes factors:
            Dayhoff     Neutral     Fitness
Dayhoff      1.0000  23145.2888      0.1244
Neutral      0.0000      1.0000      0.0000
Fitness      8.0383 186048.5842      1.0000




Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (7500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.2049  0.7951 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.2578
Fitness     Inf  3.8796  1.0000





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (7500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.2591  0.3964  0.3445 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.6535  0.7519
Neutral  1.5301  1.0000  1.1505
Fitness  1.3299  0.8692  1.0000


Posterior model probabilities (neuralnet):
Dayhoff Neutral Fitness 
 0.4973  0.0009  0.5018 

Bayes factors:
         Dayhoff  Neutral  Fitness
Dayhoff   1.0000 529.0152   0.9909
Neutral   0.0019   1.0000   0.0019
Fitness   1.0091 533.8518   1.0000




Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (7500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.2583  0.3979  0.3439 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.6491  0.7511
Neutral  1.5405  1.0000  1.1570
Fitness  1.3314  0.8643  1.0000


Posterior model probabilities (neuralnet):
Dayhoff Neutral Fitness 
 0.3214  0.0068  0.6718 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000 47.3403  0.4784
Neutral  0.0211  1.0000  0.0101
Fitness  2.0902 98.9524  1.0000




Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (7500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.2511  0.7489 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.3352
Fitness     Inf  2.9830  1.0000





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (7500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0035  0.4269  0.5696 

Bayes factors:
         Dayhoff  Neutral  Fitness
Dayhoff   1.0000   0.0081   0.0061
Neutral 123.1538   1.0000   0.7495
Fitness 164.3077   1.3342   1.0000


Posterior model probabilities (neuralnet):
Dayhoff Neutral Fitness 
 0.0000  0.0006  0.9994 

Bayes factors:
           Dayhoff    Neutral    Fitness
Dayhoff     1.0000     0.0463     0.0000
Neutral    21.6131     1.0000     0.0006
Fitness 38435.6357  1778.3474     1.0000




Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (7500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0356  0.4615  0.5029 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.0771  0.0708
Neutral 12.9625  1.0000  0.9176
Fitness 14.1273  1.0899  1.0000


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

Bayes factors:
           Dayhoff    Neutral    Fitness
Dayhoff     1.0000     1.0424     0.0001
Neutral     0.9593     1.0000     0.0001
Fitness 10657.6078 11109.9685     1.0000




Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (7500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.1531  0.8469 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.1807
Fitness     Inf  5.5331  1.0000





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (7500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.1149  0.8851 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.1299
Fitness     Inf  7.7007  1.0000





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (7500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0001  0.2856  0.7143 

Bayes factors:
          Dayhoff   Neutral   Fitness
Dayhoff    1.0000    0.0005    0.0002
Neutral 2142.0000    1.0000    0.3999
Fitness 5357.0000    2.5009    1.0000


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

Bayes factors:
            Dayhoff     Neutral     Fitness
Dayhoff      1.0000      0.8561      0.0000
Neutral      1.1681      1.0000      0.0000
Fitness 447572.1092 383165.0062      1.0000




Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (7500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.0604  0.9396 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.0643
Fitness     Inf 15.5563  1.0000





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (7500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
  0.000   0.266   0.734 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.3624
Fitness     Inf  2.7594  1.0000





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (7500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0013  0.2625  0.7361 

Bayes factors:
         Dayhoff  Neutral  Fitness
Dayhoff   1.0000   0.0051   0.0018
Neutral 196.9000   1.0000   0.3566
Fitness 552.1000   2.8040   1.0000


Posterior model probabilities (neuralnet):
Dayhoff Neutral Fitness 
 0.0002  0.0174  0.9824 

Bayes factors:
          Dayhoff   Neutral   Fitness
Dayhoff    1.0000    0.0115    0.0002
Neutral   86.9605    1.0000    0.0177
Fitness 4922.4052   56.6051    1.0000




Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (7500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0004  0.1548  0.8448 

Bayes factors:
          Dayhoff   Neutral   Fitness
Dayhoff    1.0000    0.0026    0.0005
Neutral  387.0000    1.0000    0.1832
Fitness 2112.0000    5.4574    1.0000


Posterior model probabilities (neuralnet):
Dayhoff Neutral Fitness 
 0.0000  0.0065  0.9935 

Bayes factors:
           Dayhoff    Neutral    Fitness
Dayhoff     1.0000     0.0045     0.0000
Neutral   219.8179     1.0000     0.0065
Fitness 33788.8512   153.7129     1.0000




Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (7500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.1381  0.8619 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.1603
Fitness     Inf  6.2394  1.0000





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (7500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0061  0.3655  0.6284 

Bayes factors:
         Dayhoff  Neutral  Fitness
Dayhoff   1.0000   0.0168   0.0098
Neutral  59.5870   1.0000   0.5816
Fitness 102.4565   1.7194   1.0000


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

Bayes factors:
           Dayhoff    Neutral    Fitness
Dayhoff     1.0000     1.3963     0.0000
Neutral     0.7162     1.0000     0.0000
Fitness 55055.6910 76872.1630     1.0000




Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (7500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.1447  0.8553 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.1691
Fitness     Inf  5.9124  1.0000





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (7500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.2728  0.3661  0.3611 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.7451  0.7555
Neutral  1.3421  1.0000  1.0140
Fitness  1.3236  0.9862  1.0000


Posterior model probabilities (neuralnet):
Dayhoff Neutral Fitness 
 0.3403  0.0001  0.6596 

Bayes factors:
          Dayhoff   Neutral   Fitness
Dayhoff    1.0000 5112.7569    0.5159
Neutral    0.0002    1.0000    0.0001
Fitness    1.9385 9910.9772    1.0000




Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (7500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.0792  0.9208 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.0860
Fitness     Inf 11.6263  1.0000





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (7500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.0172  0.9828 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.0175
Fitness     Inf 57.1395  1.0000





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (7500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.4148  0.5852 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.7088
Fitness     Inf  1.4108  1.0000





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (7500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.1657  0.8343 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.1987
Fitness     Inf  5.0338  1.0000





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (7500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0104  0.2651  0.7245 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.0392  0.0144
Neutral 25.4872  1.0000  0.3658
Fitness 69.6667  2.7334  1.0000


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

Bayes factors:
            Dayhoff     Neutral     Fitness
Dayhoff      1.0000      1.6356      0.0000
Neutral      0.6114      1.0000      0.0000
Fitness  86571.7155 141598.7519      1.0000




Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (7500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0137  0.5125  0.4737 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.0268  0.0290
Neutral 37.3204  1.0000  1.0819
Fitness 34.4951  0.9243  1.0000


Posterior model probabilities (neuralnet):
Dayhoff Neutral Fitness 
 0.0001  0.0017  0.9983 

Bayes factors:
           Dayhoff    Neutral    Fitness
Dayhoff     1.0000     0.0448     0.0001
Neutral    22.3150     1.0000     0.0017
Fitness 13386.9755   599.9087     1.0000




Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (7500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0200  0.5015  0.4785 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.0399  0.0418
Neutral 25.0733  1.0000  1.0479
Fitness 23.9267  0.9543  1.0000


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

Bayes factors:
            Dayhoff     Neutral     Fitness
Dayhoff      1.0000      1.2906      0.0000
Neutral      0.7748      1.0000      0.0000
Fitness 147905.3223 190885.7121      1.0000




Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (7500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.1315  0.4341  0.4344 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.3028  0.3026
Neutral  3.3022  1.0000  0.9994
Fitness  3.3043  1.0006  1.0000


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

Bayes factors:
            Dayhoff     Neutral     Fitness
Dayhoff      1.0000   2459.6390      0.0077
Neutral      0.0004      1.0000      0.0000
Fitness    129.6346 318854.3032      1.0000




Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (7500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.2612  0.3952  0.3436 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.6609  0.7602
Neutral  1.5130  1.0000  1.1502
Fitness  1.3155  0.8694  1.0000


Posterior model probabilities (neuralnet):
Dayhoff Neutral Fitness 
 0.1359  0.0003  0.8638 

Bayes factors:
          Dayhoff   Neutral   Fitness
Dayhoff    1.0000  455.7636    0.1574
Neutral    0.0022    1.0000    0.0003
Fitness    6.3545 2896.1670    1.0000




Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (7500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.0897  0.9103 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.0986
Fitness     Inf 10.1441  1.0000





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (7500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.1249  0.8751 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.1428
Fitness     Inf  7.0043  1.0000





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (7500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.2611  0.3959  0.3431 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.6595  0.7610
Neutral  1.5163  1.0000  1.1539
Fitness  1.3141  0.8666  1.0000


Posterior model probabilities (neuralnet):
Dayhoff Neutral Fitness 
 0.1329  0.0400  0.8271 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  3.3200  0.1606
Neutral  0.3012  1.0000  0.0484
Fitness  6.2252 20.6674  1.0000




Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (7500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.1573  0.8427 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.1867
Fitness     Inf  5.3559  1.0000





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (7500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.0337  0.9663 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.0349
Fitness     Inf 28.6443  1.0000





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (7500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.2535  0.3991  0.3475 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.6351  0.7295
Neutral  1.5744  1.0000  1.1485
Fitness  1.3709  0.8707  1.0000


Posterior model probabilities (neuralnet):
Dayhoff Neutral Fitness 
 0.2132  0.2703  0.5165 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.7888  0.4129
Neutral  1.2678  1.0000  0.5234
Fitness  2.4222  1.9105  1.0000




Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (7500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.0259  0.9741 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.0266
Fitness     Inf 37.6598  1.0000





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (7500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.1369  0.8631 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.1587
Fitness     Inf  6.3028  1.0000





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (7500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.2081  0.3693  0.4225 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.5635  0.4926
Neutral  1.7745  1.0000  0.8741
Fitness  2.0301  1.1440  1.0000


Posterior model probabilities (neuralnet):
Dayhoff Neutral Fitness 
 0.0083  0.0004  0.9912 

Bayes factors:
          Dayhoff   Neutral   Fitness
Dayhoff    1.0000   18.5994    0.0084
Neutral    0.0538    1.0000    0.0005
Fitness  118.9863 2213.0733    1.0000




Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (7500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0060  0.2617  0.7323 

Bayes factors:
         Dayhoff  Neutral  Fitness
Dayhoff   1.0000   0.0229   0.0082
Neutral  43.6222   1.0000   0.3574
Fitness 122.0444   2.7978   1.0000


Posterior model probabilities (neuralnet):
Dayhoff Neutral Fitness 
 0.0008  0.0333  0.9659 

Bayes factors:
          Dayhoff   Neutral   Fitness
Dayhoff    1.0000    0.0245    0.0008
Neutral   40.7874    1.0000    0.0344
Fitness 1184.4037   29.0385    1.0000




Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (7500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.2579  0.4005  0.3416 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.6438  0.7549
Neutral  1.5533  1.0000  1.1725
Fitness  1.3247  0.8529  1.0000


Posterior model probabilities (neuralnet):
Dayhoff Neutral Fitness 
 0.0692  0.0006  0.9302 

Bayes factors:
          Dayhoff   Neutral   Fitness
Dayhoff    1.0000  112.7273    0.0744
Neutral    0.0089    1.0000    0.0007
Fitness   13.4392 1514.9651    1.0000




Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (7500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0692  0.4015  0.5293 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.1724  0.1307
Neutral  5.8015  1.0000  0.7584
Fitness  7.6493  1.3185  1.0000


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

Bayes factors:
           Dayhoff    Neutral    Fitness
Dayhoff     1.0000     4.7783     0.0002
Neutral     0.2093     1.0000     0.0001
Fitness  4067.6573 19436.2875     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 (7500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.0953  0.9047 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.1054
Fitness     Inf  9.4895  1.0000





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (7500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.2595  0.3739  0.3667 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.6940  0.7076
Neutral  1.4409  1.0000  1.0196
Fitness  1.4132  0.9807  1.0000


Posterior model probabilities (neuralnet):
Dayhoff Neutral Fitness 
 0.0595  0.0000  0.9405 

Bayes factors:
           Dayhoff    Neutral    Fitness
Dayhoff     1.0000  3975.5142     0.0633
Neutral     0.0003     1.0000     0.0000
Fitness    15.8035 62827.1576     1.0000




Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (7500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.2104  0.4137  0.3759 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.5085  0.5598
Neutral  1.9664  1.0000  1.1007
Fitness  1.7864  0.9085  1.0000


Posterior model probabilities (neuralnet):
Dayhoff Neutral Fitness 
 0.0211  0.0000  0.9789 

Bayes factors:
           Dayhoff    Neutral    Fitness
Dayhoff     1.0000   686.1171     0.0215
Neutral     0.0015     1.0000     0.0000
Fitness    46.4554 31873.8532     1.0000




Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (7500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.0352  0.9648 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.0365
Fitness     Inf 27.4091  1.0000





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (7500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.4432  0.5568 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.7960
Fitness     Inf  1.2563  1.0000





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (7500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.1384  0.8616 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.1606
Fitness     Inf  6.2254  1.0000





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (7500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.0231  0.9769 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.0236
Fitness     Inf 42.3526  1.0000





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (7500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0081  0.0928  0.8991 

Bayes factors:
         Dayhoff  Neutral  Fitness
Dayhoff   1.0000   0.0876   0.0090
Neutral  11.4098   1.0000   0.1032
Fitness 110.5410   9.6882   1.0000


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

Bayes factors:
            Dayhoff     Neutral     Fitness
Dayhoff      1.0000     12.7699      0.0000
Neutral      0.0783      1.0000      0.0000
Fitness  48875.5749 624135.4764      1.0000




Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (7500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.0269  0.9731 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.0277
Fitness     Inf 36.1287  1.0000





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (7500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.0407  0.9593 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.0424
Fitness     Inf 23.5902  1.0000





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (7500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.3368  0.6632 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.5078
Fitness     Inf  1.9691  1.0000





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (7500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0044  0.4393  0.5563 

Bayes factors:
         Dayhoff  Neutral  Fitness
Dayhoff   1.0000   0.0100   0.0079
Neutral  99.8485   1.0000   0.7898
Fitness 126.4242   1.2662   1.0000


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

Bayes factors:
             Dayhoff      Neutral      Fitness
Dayhoff       1.0000       5.0217       0.0000
Neutral       0.1991       1.0000       0.0000
Fitness  250094.9785 1255892.0758       1.0000




Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (7500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
  0.000   0.182   0.818 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.2225
Fitness     Inf  4.4945  1.0000





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (7500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.4128  0.5872 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.7030
Fitness     Inf  1.4225  1.0000





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (7500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.1579  0.8421 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.1875
Fitness     Inf  5.3345  1.0000





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (7500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.2384  0.7616 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.3130
Fitness     Inf  3.1946  1.0000





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (7500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.2861  0.3307  0.3832 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.8653  0.7467
Neutral  1.1556  1.0000  0.8629
Fitness  1.3392  1.1589  1.0000


Posterior model probabilities (neuralnet):
Dayhoff Neutral Fitness 
 0.3059  0.0000  0.6941 

Bayes factors:
           Dayhoff    Neutral    Fitness
Dayhoff     1.0000 34199.1033     0.4408
Neutral     0.0000     1.0000     0.0000
Fitness     2.2688 77589.3123     1.0000




Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (7500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.1483  0.8517 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.1741
Fitness     Inf  5.7446  1.0000





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (7500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.1079  0.3437  0.5484 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.3138  0.1967
Neutral  3.1867  1.0000  0.6268
Fitness  5.0841  1.5954  1.0000


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

Bayes factors:
            Dayhoff     Neutral     Fitness
Dayhoff      1.0000    109.5673      0.0010
Neutral      0.0091      1.0000      0.0000
Fitness    967.9751 106058.4363      1.0000




Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (7500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.1776  0.4277  0.3947 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.4152  0.4500
Neutral  2.4084  1.0000  1.0838
Fitness  2.2222  0.9227  1.0000


Posterior model probabilities (neuralnet):
Dayhoff Neutral Fitness 
 0.0083  0.0000  0.9917 

Bayes factors:
           Dayhoff    Neutral    Fitness
Dayhoff     1.0000   323.2700     0.0083
Neutral     0.0031     1.0000     0.0000
Fitness   119.8914 38757.2918     1.0000




Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (7500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.1293  0.8707 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.1485
Fitness     Inf  6.7320  1.0000





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (7500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.0693  0.9307 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.0745
Fitness     Inf 13.4231  1.0000





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (7500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.3383  0.6617 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.5112
Fitness     Inf  1.9562  1.0000





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (7500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.2571  0.3980  0.3449 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.6459  0.7453
Neutral  1.5482  1.0000  1.1538
Fitness  1.3418  0.8667  1.0000


Posterior model probabilities (neuralnet):
Dayhoff Neutral Fitness 
 0.3631  0.0099  0.6270 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000 36.5857  0.5790
Neutral  0.0273  1.0000  0.0158
Fitness  1.7271 63.1861  1.0000




Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (7500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.0909  0.9091 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.1000
Fitness     Inf  9.9971  1.0000





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (7500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.0603  0.9397 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.0641
Fitness     Inf 15.5929  1.0000





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (7500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0025  0.4627  0.5348 

Bayes factors:
         Dayhoff  Neutral  Fitness
Dayhoff   1.0000   0.0055   0.0047
Neutral 182.6316   1.0000   0.8651
Fitness 211.1053   1.1559   1.0000


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

Bayes factors:
            Dayhoff     Neutral     Fitness
Dayhoff      1.0000      3.3753      0.0000
Neutral      0.2963      1.0000      0.0000
Fitness  56666.3834 191264.3747      1.0000




Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (7500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.0468  0.9532 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.0491
Fitness     Inf 20.3675  1.0000





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (7500 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 (7500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0971  0.4621  0.4408 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.2100  0.2202
Neutral  4.7610  1.0000  1.0484
Fitness  4.5412  0.9538  1.0000


Posterior model probabilities (neuralnet):
Dayhoff Neutral Fitness 
  0.007   0.045   0.948 

Bayes factors:
         Dayhoff  Neutral  Fitness
Dayhoff   1.0000   0.1553   0.0074
Neutral   6.4377   1.0000   0.0475
Fitness 135.6719  21.0746   1.0000




Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (7500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0280  0.3591  0.6129 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.0780  0.0457
Neutral 12.8238  1.0000  0.5858
Fitness 21.8905  1.7070  1.0000


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

Bayes factors:
             Dayhoff      Neutral      Fitness
Dayhoff       1.0000     132.3868       0.0001
Neutral       0.0076       1.0000       0.0000
Fitness   10293.7137 1362751.7286       1.0000




