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      92       0       8
Neutral       0      99       1
Fitness       2       4      94


Mean model posterior probabilities (neuralnet)

$tol0.05
        Dayhoff Neutral Fitness
Dayhoff  0.9230  0.0021  0.0749
Neutral  0.0018  0.8932  0.1050
Fitness  0.0388  0.1055  0.8557




Model 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 
 0.3556  0.2277  0.4167 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  1.5615  0.8534
Neutral  0.6404  1.0000  0.5466
Fitness  1.1717  1.8296  1.0000


Posterior model probabilities (neuralnet):
Dayhoff Neutral Fitness 
 0.9401  0.0000  0.0599 

Bayes factors:
             Dayhoff      Neutral      Fitness
Dayhoff 1.000000e+00 3.030723e+07 1.569080e+01
Neutral 0.000000e+00 1.000000e+00 0.000000e+00
Fitness 6.370000e-02 1.931523e+06 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 
      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 (7500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.4380  0.0035  0.5585 

Bayes factors:
         Dayhoff  Neutral  Fitness
Dayhoff   1.0000 126.3462   0.7842
Neutral   0.0079   1.0000   0.0062
Fitness   1.2752 161.1154   1.0000


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

Bayes factors:
             Dayhoff      Neutral      Fitness
Dayhoff 1.000000e+00 3.228939e+09 1.843752e+06
Neutral 0.000000e+00 1.000000e+00 6.000000e-04
Fitness 0.000000e+00 1.751287e+03 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 
      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 (7500 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 (7500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.9779  0.0000  0.0221 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000     Inf 44.1807
Neutral  0.0000          0.0000
Fitness  0.0226     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 (7500 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 (7500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.9872  0.0000  0.0128 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff   1.000     Inf  77.125
Neutral   0.000           0.000
Fitness   0.013     Inf   1.000





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.9612  0.0000  0.0388 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000     Inf 24.7732
Neutral  0.0000          0.0000
Fitness  0.0404     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 (7500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.5320  0.0692  0.3988 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  7.6879  1.3340
Neutral  0.1301  1.0000  0.1735
Fitness  0.7496  5.7630  1.0000


Posterior model probabilities (neuralnet):
Dayhoff Neutral Fitness 
  0.998   0.000   0.002 

Bayes factors:
             Dayhoff      Neutral      Fitness
Dayhoff 1.000000e+00 2.425218e+07 4.963008e+02
Neutral 0.000000e+00 1.000000e+00 0.000000e+00
Fitness 2.000000e-03 4.886590e+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 (7500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.2695  0.3843  0.3463 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.7012  0.7782
Neutral  1.4260  1.0000  1.1097
Fitness  1.2850  0.9011  1.0000


Posterior model probabilities (neuralnet):
Dayhoff Neutral Fitness 
 0.1943  0.0001  0.8056 

Bayes factors:
           Dayhoff    Neutral    Fitness
Dayhoff     1.0000  3662.3819     0.2412
Neutral     0.0003     1.0000     0.0001
Fitness     4.1457 15182.9589     1.0000




Model 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 
 0.8851  0.0000  0.1149 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000     Inf  7.7007
Neutral  0.0000          0.0000
Fitness  0.1299     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 (7500 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 (7500 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 (7500 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 (7500 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 (7500 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 (7500 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 (7500 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 (7500 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 (7500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.4908  0.0041  0.5051 

Bayes factors:
         Dayhoff  Neutral  Fitness
Dayhoff   1.0000 118.7419   0.9718
Neutral   0.0084   1.0000   0.0082
Fitness   1.0291 122.1935   1.0000


Posterior model probabilities (neuralnet):
Dayhoff Neutral Fitness 
 0.9605  0.0001  0.0394 

Bayes factors:
           Dayhoff    Neutral    Fitness
Dayhoff     1.0000 10187.6759    24.3993
Neutral     0.0001     1.0000     0.0024
Fitness     0.0410   417.5396     1.0000




Model 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 
      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 (7500 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 (7500 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 (7500 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 (7500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.8045  0.0003  0.1952 

Bayes factors:
          Dayhoff   Neutral   Fitness
Dayhoff    1.0000 3017.0000    4.1216
Neutral    0.0003    1.0000    0.0014
Fitness    0.2426  732.0000    1.0000


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

Bayes factors:
             Dayhoff      Neutral      Fitness
Dayhoff       1.0000 4078198.3885 1430318.3475
Neutral       0.0000       1.0000       0.3507
Fitness       0.0000       2.8513       1.0000




Model 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 
      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 (7500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.9915  0.0000  0.0085 

Bayes factors:
         Dayhoff  Neutral  Fitness
Dayhoff   1.0000      Inf 116.1875
Neutral   0.0000            0.0000
Fitness   0.0086      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 (7500 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 (7500 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 (7500 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 (7500 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 (7500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.8720  0.0001  0.1279 

Bayes factors:
          Dayhoff   Neutral   Fitness
Dayhoff    1.0000 6540.0000    6.8196
Neutral    0.0002    1.0000    0.0010
Fitness    0.1466  959.0000    1.0000


Posterior model probabilities (neuralnet):
Dayhoff Neutral Fitness 
 0.9946  0.0000  0.0054 

Bayes factors:
            Dayhoff     Neutral     Fitness
Dayhoff      1.0000 226239.4401    183.7579
Neutral      0.0000      1.0000      0.0008
Fitness      0.0054   1231.1820      1.0000




Model 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 
 0.5415  0.0103  0.4483 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000 52.7403  1.2079
Neutral  0.0190  1.0000  0.0229
Fitness  0.8279 43.6623  1.0000


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

Bayes factors:
             Dayhoff      Neutral      Fitness
Dayhoff 1.000000e+00 4.807879e+09 8.796735e+03
Neutral 0.000000e+00 1.000000e+00 0.000000e+00
Fitness 1.000000e-04 5.465527e+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 (7500 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 (7500 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 (7500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

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

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000     Inf 14.6904
Neutral  0.0000          0.0000
Fitness  0.0681     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 (7500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.7148  0.0001  0.2851 

Bayes factors:
          Dayhoff   Neutral   Fitness
Dayhoff    1.0000 5361.0000    2.5075
Neutral    0.0002    1.0000    0.0005
Fitness    0.3988 2138.0000    1.0000


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

Bayes factors:
             Dayhoff      Neutral      Fitness
Dayhoff       1.0000 2405334.4553 1654333.0410
Neutral       0.0000       1.0000       0.6878
Fitness       0.0000       1.4540       1.0000




Model 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 
 0.9583  0.0000  0.0417 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000     Inf 22.9617
Neutral  0.0000          0.0000
Fitness  0.0436     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 (7500 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 (7500 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 (7500 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 (7500 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 (7500 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 (7500 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 (7500 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 (7500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.2536  0.3991  0.3473 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.6355  0.7301
Neutral  1.5736  1.0000  1.1489
Fitness  1.3696  0.8704  1.0000


Posterior model probabilities (neuralnet):
Dayhoff Neutral Fitness 
 0.4166  0.0098  0.5736 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000 42.7229  0.7263
Neutral  0.0234  1.0000  0.0170
Fitness  1.3768 58.8209  1.0000




Model 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 
      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 (7500 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 (7500 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 (7500 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 (7500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.4405  0.1656  0.3939 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  2.6602  1.1185
Neutral  0.3759  1.0000  0.4204
Fitness  0.8941  2.3784  1.0000


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

Bayes factors:
             Dayhoff      Neutral      Fitness
Dayhoff 1.000000e+00 2.722533e+08 4.164221e+05
Neutral 0.000000e+00 1.000000e+00 1.500000e-03
Fitness 0.000000e+00 6.537916e+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 (7500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.2101  0.1269  0.6629 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  1.6555  0.3170
Neutral  0.6041  1.0000  0.1915
Fitness  3.1548  5.2227  1.0000


Posterior model probabilities (neuralnet):
Dayhoff Neutral Fitness 
 0.9832  0.0000  0.0168 

Bayes factors:
             Dayhoff      Neutral      Fitness
Dayhoff       1.0000 4407947.5705      58.6005
Neutral       0.0000       1.0000       0.0000
Fitness       0.0171   75220.3591       1.0000




Model 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 
      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 (7500 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 (7500 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 (7500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.7889  0.0008  0.2103 

Bayes factors:
         Dayhoff  Neutral  Fitness
Dayhoff   1.0000 986.1667   3.7521
Neutral   0.0010   1.0000   0.0038
Fitness   0.2665 262.8333   1.0000


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

Bayes factors:
             Dayhoff      Neutral      Fitness
Dayhoff 1.000000e+00 7.086019e+07 1.557130e+04
Neutral 0.000000e+00 1.000000e+00 2.000000e-04
Fitness 1.000000e-04 4.550692e+03 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 
      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 (7500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.9999  0.0000  0.0001 

Bayes factors:
          Dayhoff   Neutral   Fitness
Dayhoff    1.0000       Inf 7499.0000
Neutral    0.0000              0.0000
Fitness    0.0001       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 (7500 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 (7500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.2461  0.3783  0.3756 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.6507  0.6553
Neutral  1.5368  1.0000  1.0071
Fitness  1.5260  0.9930  1.0000


Posterior model probabilities (neuralnet):
Dayhoff Neutral Fitness 
 0.1291  0.0231  0.8478 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  5.5786  0.1523
Neutral  0.1793  1.0000  0.0273
Fitness  6.5680 36.6399  1.0000




Model 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 
      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 (7500 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 (7500 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 (7500 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 (7500 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 (7500 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 (7500 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 (7500 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 (7500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.2539  0.4000  0.3461 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.6347  0.7334
Neutral  1.5756  1.0000  1.1556
Fitness  1.3634  0.8653  1.0000


Posterior model probabilities (neuralnet):
Dayhoff Neutral Fitness 
 0.4560  0.1079  0.4361 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  4.2259  1.0456
Neutral  0.2366  1.0000  0.2474
Fitness  0.9564  4.0418  1.0000




Model 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 
      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 (7500 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 (7500 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 (7500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.4633  0.0053  0.5313 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000 86.8750  0.8720
Neutral  0.0115  1.0000  0.0100
Fitness  1.1468 99.6250  1.0000


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

Bayes factors:
             Dayhoff      Neutral      Fitness
Dayhoff 1.000000e+00 5.167034e+07 3.524412e+04
Neutral 0.000000e+00 1.000000e+00 7.000000e-04
Fitness 0.000000e+00 1.466070e+03 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 
      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 (7500 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 (7500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

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

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000     Inf  5.0338
Neutral  0.0000          0.0000
Fitness  0.1987     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 (7500 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 (7500 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 (7500 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 (7500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.9276  0.0000  0.0724 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000     Inf 12.8122
Neutral  0.0000          0.0000
Fitness  0.0781     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 (7500 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 (7500 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 (7500 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 (7500 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 (7500 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 (7500 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 (7500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.5307  0.0584  0.4109 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  9.0868  1.2914
Neutral  0.1101  1.0000  0.1421
Fitness  0.7744  7.0365  1.0000


Posterior model probabilities (neuralnet):
Dayhoff Neutral Fitness 
 0.9959  0.0000  0.0041 

Bayes factors:
             Dayhoff      Neutral      Fitness
Dayhoff 1.000000e+00 3.175973e+07 2.427726e+02
Neutral 0.000000e+00 1.000000e+00 0.000000e+00
Fitness 4.100000e-03 1.308209e+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 (7500 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 (7500 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 (7500 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 (7500 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 (7500 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 (7500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.9848  0.0000  0.0152 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000     Inf 64.7895
Neutral  0.0000          0.0000
Fitness  0.0154     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 (7500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.4547  0.1028  0.4425 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  4.4228  1.0274
Neutral  0.2261  1.0000  0.2323
Fitness  0.9733  4.3048  1.0000


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

Bayes factors:
             Dayhoff      Neutral      Fitness
Dayhoff 1.000000e+00 1.603600e+09 3.819188e+03
Neutral 0.000000e+00 1.000000e+00 0.000000e+00
Fitness 3.000000e-04 4.198797e+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 (7500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.9981  0.0000  0.0019 

Bayes factors:
         Dayhoff  Neutral  Fitness
Dayhoff   1.0000      Inf 534.7143
Neutral   0.0000            0.0000
Fitness   0.0019      Inf   1.0000





