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      96       1       3
Neutral       1      96       3
Fitness       1       2      97


Mean model posterior probabilities (neuralnet)

$tol0.05
        Dayhoff Neutral Fitness
Dayhoff  0.9415  0.0050  0.0534
Neutral  0.0057  0.8439  0.1504
Fitness  0.0269  0.1240  0.8492




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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.3713  0.2407  0.3880 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  1.5429  0.9570
Neutral  0.6481  1.0000  0.6203
Fitness  1.0449  1.6122  1.0000


Posterior model probabilities (neuralnet):
Dayhoff Neutral Fitness 
  0.986   0.000   0.014 

Bayes factors:
             Dayhoff      Neutral      Fitness
Dayhoff       1.0000 4693849.2126      70.5931
Neutral       0.0000       1.0000       0.0000
Fitness       0.0142   66491.6156       1.0000




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

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

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





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.4213  0.0033  0.5753 

Bayes factors:
         Dayhoff  Neutral  Fitness
Dayhoff   1.0000 126.4000   0.7323
Neutral   0.0079   1.0000   0.0058
Fitness   1.3655 172.6000   1.0000


Posterior model probabilities (neuralnet):
Dayhoff Neutral Fitness 
 0.9534  0.0000  0.0466 

Bayes factors:
           Dayhoff    Neutral    Fitness
Dayhoff     1.0000 29011.6234    20.4613
Neutral     0.0000     1.0000     0.0007
Fitness     0.0489  1417.8810     1.0000




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

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

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





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

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

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





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

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

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000     Inf 39.5405
Neutral  0.0000          0.0000
Fitness  0.0253     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 (1500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

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

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





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
  0.982   0.000   0.018 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000     Inf 54.5556
Neutral  0.0000          0.0000
Fitness  0.0183     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 (1500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

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

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





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

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

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





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

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

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





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

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

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





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

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

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000     Inf 21.3881
Neutral  0.0000          0.0000
Fitness  0.0468     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 (1500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.5453  0.0787  0.3760 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  6.9322  1.4504
Neutral  0.1443  1.0000  0.2092
Fitness  0.6895  4.7797  1.0000


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

Bayes factors:
             Dayhoff      Neutral      Fitness
Dayhoff 1.000000e+00 1.667648e+07 1.027697e+03
Neutral 0.000000e+00 1.000000e+00 1.000000e-04
Fitness 1.000000e-03 1.622704e+04 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 (1500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
  0.276   0.388   0.336 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.7113  0.8214
Neutral  1.4058  1.0000  1.1548
Fitness  1.2174  0.8660  1.0000


Posterior model probabilities (neuralnet):
Dayhoff Neutral Fitness 
 0.1943  0.0000  0.8057 

Bayes factors:
           Dayhoff    Neutral    Fitness
Dayhoff     1.0000 15871.3050     0.2411
Neutral     0.0001     1.0000     0.0000
Fitness     4.1469 65815.9677     1.0000




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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
  0.872   0.000   0.128 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000     Inf  6.8125
Neutral  0.0000          0.0000
Fitness  0.1468     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 (1500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

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

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





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

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

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





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

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

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





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

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

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





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

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

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





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

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

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





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

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

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





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

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

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





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.4800  0.0087  0.5113 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000 55.3846  0.9387
Neutral  0.0181  1.0000  0.0169
Fitness  1.0653 59.0000  1.0000


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

Bayes factors:
             Dayhoff      Neutral      Fitness
Dayhoff 1.000000e+00 1.219200e+07 4.236785e+04
Neutral 0.000000e+00 1.000000e+00 3.500000e-03
Fitness 0.000000e+00 2.877653e+02 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 (1500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

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

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





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

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

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





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

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

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





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

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

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





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.8000  0.0007  0.1993 

Bayes factors:
          Dayhoff   Neutral   Fitness
Dayhoff    1.0000 1200.0000    4.0134
Neutral    0.0008    1.0000    0.0033
Fitness    0.2492  299.0000    1.0000


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

Bayes factors:
             Dayhoff      Neutral      Fitness
Dayhoff       1.0000 1033748.2935   95703.6984
Neutral       0.0000       1.0000       0.0926
Fitness       0.0000      10.8016       1.0000




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

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

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





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.9893  0.0000  0.0107 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000     Inf 92.7500
Neutral  0.0000          0.0000
Fitness  0.0108     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 (1500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

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

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





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

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

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





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

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

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





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

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

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





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.8593  0.0000  0.1407 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000     Inf  6.1090
Neutral  0.0000          0.0000
Fitness  0.1637     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 (1500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.5380  0.0147  0.4473 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000 36.6818  1.2027
Neutral  0.0273  1.0000  0.0328
Fitness  0.8315 30.5000  1.0000


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

Bayes factors:
            Dayhoff     Neutral     Fitness
Dayhoff      1.0000 894549.5271  14038.0797
Neutral      0.0000      1.0000      0.0157
Fitness      0.0001     63.7231      1.0000




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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.9993  0.0000  0.0007 

Bayes factors:
          Dayhoff   Neutral   Fitness
Dayhoff    1.0000       Inf 1499.0000
Neutral    0.0000              0.0000
Fitness    0.0007       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 (1500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

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

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





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.9353  0.0000  0.0647 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000     Inf 14.4639
Neutral  0.0000          0.0000
Fitness  0.0691     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 (1500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.6953  0.0007  0.3040 

Bayes factors:
          Dayhoff   Neutral   Fitness
Dayhoff    1.0000 1043.0000    2.2873
Neutral    0.0010    1.0000    0.0022
Fitness    0.4372  456.0000    1.0000


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

Bayes factors:
             Dayhoff      Neutral      Fitness
Dayhoff 1.000000e+00 6.259263e+06 2.891366e+07
Neutral 0.000000e+00 1.000000e+00 4.619300e+00
Fitness 0.000000e+00 2.165000e-01 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 (1500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.9507  0.0000  0.0493 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000     Inf 19.2703
Neutral  0.0000          0.0000
Fitness  0.0519     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 (1500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

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

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





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

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

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





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

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

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





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

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

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





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

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

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





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

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

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





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

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

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





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.2573  0.4133  0.3293 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.6226  0.7814
Neutral  1.6062  1.0000  1.2551
Fitness  1.2798  0.7968  1.0000


Posterior model probabilities (neuralnet):
Dayhoff Neutral Fitness 
 0.4384  0.0074  0.5543 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000 59.5569  0.7908
Neutral  0.0168  1.0000  0.0133
Fitness  1.2645 75.3088  1.0000




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

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

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





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

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

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





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

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

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000     Inf 99.0000
Neutral  0.0000          0.0000
Fitness  0.0101     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 (1500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

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

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





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.4560  0.1613  0.3827 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  2.8264  1.1916
Neutral  0.3538  1.0000  0.4216
Fitness  0.8392  2.3719  1.0000


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

Bayes factors:
             Dayhoff      Neutral      Fitness
Dayhoff 1.000000e+00 3.859780e+08 3.943361e+03
Neutral 0.000000e+00 1.000000e+00 0.000000e+00
Fitness 3.000000e-04 9.788048e+04 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 (1500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.2153  0.1300  0.6547 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  1.6564  0.3289
Neutral  0.6037  1.0000  0.1986
Fitness  3.0402  5.0359  1.0000


Posterior model probabilities (neuralnet):
Dayhoff Neutral Fitness 
 0.9818  0.0000  0.0181 

Bayes factors:
           Dayhoff    Neutral    Fitness
Dayhoff     1.0000 37456.2575    54.1436
Neutral     0.0000     1.0000     0.0014
Fitness     0.0185   691.7946     1.0000




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

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

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





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

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

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





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

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

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





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.7867  0.0000  0.2133 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000     Inf  3.6875
Neutral  0.0000          0.0000
Fitness  0.2712     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 (1500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

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

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





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.9993  0.0000  0.0007 

Bayes factors:
          Dayhoff   Neutral   Fitness
Dayhoff    1.0000       Inf 1499.0000
Neutral    0.0000              0.0000
Fitness    0.0007       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 (1500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

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

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





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.2493  0.3920  0.3587 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.6361  0.6952
Neutral  1.5722  1.0000  1.0929
Fitness  1.4385  0.9150  1.0000


Posterior model probabilities (neuralnet):
Dayhoff Neutral Fitness 
 0.1224  0.0797  0.7979 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  1.5364  0.1534
Neutral  0.6509  1.0000  0.0999
Fitness  6.5170 10.0129  1.0000




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

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

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





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

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

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





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

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

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





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

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

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





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

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

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





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

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

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





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

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

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





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

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

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





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
  0.264   0.398   0.338 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.6633  0.7811
Neutral  1.5076  1.0000  1.1775
Fitness  1.2803  0.8492  1.0000


Posterior model probabilities (neuralnet):
Dayhoff Neutral Fitness 
 0.4682  0.3121  0.2197 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  1.5003  2.1313
Neutral  0.6665  1.0000  1.4205
Fitness  0.4692  0.7040  1.0000




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

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

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





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

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

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





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

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

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





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.4547  0.0080  0.5373 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000 56.8333  0.8462
Neutral  0.0176  1.0000  0.0149
Fitness  1.1818 67.1667  1.0000


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

Bayes factors:
             Dayhoff      Neutral      Fitness
Dayhoff       1.0000 6272750.5930  276714.1912
Neutral       0.0000       1.0000       0.0441
Fitness       0.0000      22.6687       1.0000




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

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

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





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

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

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





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
  0.814   0.000   0.186 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000     Inf  4.3763
Neutral  0.0000          0.0000
Fitness  0.2285     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 (1500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

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

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





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

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

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





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

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

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





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.9193  0.0000  0.0807 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000     Inf 11.3967
Neutral  0.0000          0.0000
Fitness  0.0877     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 (1500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

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

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





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

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

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





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

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

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





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

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

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





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

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

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





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

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

Bayes factors:
         Dayhoff  Neutral  Fitness
Dayhoff   1.0000      Inf 749.0000
Neutral   0.0000            0.0000
Fitness   0.0013      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 (1500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.5280  0.0673  0.4047 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  7.8416  1.3048
Neutral  0.1275  1.0000  0.1664
Fitness  0.7664  6.0099  1.0000


Posterior model probabilities (neuralnet):
Dayhoff Neutral Fitness 
 0.9884  0.0000  0.0116 

Bayes factors:
             Dayhoff      Neutral      Fitness
Dayhoff 1.000000e+00 1.175409e+07 8.540510e+01
Neutral 0.000000e+00 1.000000e+00 0.000000e+00
Fitness 1.170000e-02 1.376275e+05 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 (1500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

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

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





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

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

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





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

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

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





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

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

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





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

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

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





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

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

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000     Inf 70.4286
Neutral  0.0000          0.0000
Fitness  0.0142     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 (1500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.4440  0.1027  0.4533 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  4.3247  0.9794
Neutral  0.2312  1.0000  0.2265
Fitness  1.0210  4.4156  1.0000


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

Bayes factors:
             Dayhoff      Neutral      Fitness
Dayhoff       1.0000 7312967.4642    1696.6466
Neutral       0.0000       1.0000       0.0002
Fitness       0.0006    4310.2478       1.0000




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

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

Bayes factors:
         Dayhoff  Neutral  Fitness
Dayhoff   1.0000      Inf 374.0000
Neutral   0.0000            0.0000
Fitness   0.0027      Inf   1.0000





