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

$tol0.05
        Dayhoff Neutral Fitness
Dayhoff      97       0       3
Neutral       0      99       1
Fitness       0       1      99


Mean model posterior probabilities (mnlogistic)

$tol0.05
        Dayhoff Neutral Fitness
Dayhoff  0.9508  0.0012  0.0480
Neutral  0.0044  0.8763  0.1193
Fitness  0.0221  0.1178  0.8601




Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (15000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.3503  0.2372  0.4125 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  1.4770  0.8494
Neutral  0.6771  1.0000  0.5751
Fitness  1.1774  1.7389  1.0000


Posterior model probabilities (mnlogistic):
Dayhoff Neutral Fitness 
 0.9373  0.0000  0.0627 

Bayes factors:
             Dayhoff      Neutral      Fitness
Dayhoff 1.000000e+00 6.396497e+13 1.495940e+01
Neutral 0.000000e+00 1.000000e+00 0.000000e+00
Fitness 6.680000e-02 4.275892e+12 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 (15000 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 (15000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.4413  0.0027  0.5561 

Bayes factors:
         Dayhoff  Neutral  Fitness
Dayhoff   1.0000 165.4750   0.7935
Neutral   0.0060   1.0000   0.0048
Fitness   1.2602 208.5250   1.0000


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

Bayes factors:
             Dayhoff      Neutral      Fitness
Dayhoff 1.000000e+00 4.372433e+62 4.320762e+07
Neutral 0.000000e+00 1.000000e+00 0.000000e+00
Fitness 0.000000e+00 1.011959e+55 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 (15000 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 (15000 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 (15000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.9767  0.0000  0.0233 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000     Inf 41.9799
Neutral  0.0000          0.0000
Fitness  0.0238     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 (15000 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 (15000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.9865  0.0000  0.0135 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000     Inf 73.2574
Neutral  0.0000          0.0000
Fitness  0.0137     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 (15000 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 (15000 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 (15000 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 (15000 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 (15000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.9609  0.0000  0.0391 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000     Inf 24.5537
Neutral  0.0000          0.0000
Fitness  0.0407     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 (15000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.5277  0.0764  0.3959 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  6.9075  1.3331
Neutral  0.1448  1.0000  0.1930
Fitness  0.7501  5.1815  1.0000


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

Bayes factors:
             Dayhoff      Neutral      Fitness
Dayhoff 1.000000e+00 1.102268e+24 4.493306e+03
Neutral 0.000000e+00 1.000000e+00 0.000000e+00
Fitness 2.000000e-04 2.453135e+20 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 (15000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
  0.272   0.380   0.348 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.7158  0.7816
Neutral  1.3971  1.0000  1.0920
Fitness  1.2794  0.9158  1.0000


Posterior model probabilities (mnlogistic):
Dayhoff Neutral Fitness 
 0.2229  0.0000  0.7771 

Bayes factors:
           Dayhoff    Neutral    Fitness
Dayhoff     1.0000  7635.4147     0.2868
Neutral     0.0001     1.0000     0.0000
Fitness     3.4863 26619.0824     1.0000




Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (15000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.8877  0.0001  0.1123 

Bayes factors:
           Dayhoff    Neutral    Fitness
Dayhoff     1.0000 13315.0000     7.9068
Neutral     0.0001     1.0000     0.0006
Fitness     0.1265  1684.0000     1.0000


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

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff       1       1       1
Neutral       1       1       1
Fitness       1       1       1




Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (15000 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 (15000 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 (15000 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 (15000 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 (15000 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 (15000 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 (15000 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 (15000 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 (15000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.4937  0.0057  0.5006 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000 87.1294  0.9863
Neutral  0.0115  1.0000  0.0113
Fitness  1.0139 88.3412  1.0000


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

Bayes factors:
             Dayhoff      Neutral      Fitness
Dayhoff 1.000000e+00 1.089972e+38 6.866662e+04
Neutral 0.000000e+00 1.000000e+00 0.000000e+00
Fitness 0.000000e+00 1.587339e+33 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 (15000 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 (15000 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 (15000 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 (15000 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 (15000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.8097  0.0004  0.1899 

Bayes factors:
          Dayhoff   Neutral   Fitness
Dayhoff    1.0000 2024.1667    4.2629
Neutral    0.0005    1.0000    0.0021
Fitness    0.2346  474.8333    1.0000


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

Bayes factors:
             Dayhoff      Neutral      Fitness
Dayhoff 1.000000e+00 4.026019e+40 6.468717e+05
Neutral 0.000000e+00 1.000000e+00 0.000000e+00
Fitness 0.000000e+00 6.223829e+34 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 (15000 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 (15000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.9921  0.0000  0.0079 

Bayes factors:
         Dayhoff  Neutral  Fitness
Dayhoff   1.0000      Inf 125.0504
Neutral   0.0000            0.0000
Fitness   0.0080      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 (15000 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 (15000 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 (15000 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 (15000 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 (15000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.8735  0.0001  0.1263 

Bayes factors:
          Dayhoff   Neutral   Fitness
Dayhoff    1.0000 6551.5000    6.9145
Neutral    0.0002    1.0000    0.0011
Fitness    0.1446  947.5000    1.0000


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

Bayes factors:
              Dayhoff       Neutral       Fitness
Dayhoff  1.000000e+00 1.490445e+163  3.163743e+06
Neutral  0.000000e+00  1.000000e+00  0.000000e+00
Fitness  0.000000e+00 4.711019e+156  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 (15000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.5465  0.0139  0.4396 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000 39.2201  1.2431
Neutral  0.0255  1.0000  0.0317
Fitness  0.8044 31.5502  1.0000


Posterior model probabilities (mnlogistic):
Dayhoff Neutral Fitness 
 0.9995  0.0000  0.0005 

Bayes factors:
             Dayhoff      Neutral      Fitness
Dayhoff 1.000000e+00 2.200696e+22 2.207267e+03
Neutral 0.000000e+00 1.000000e+00 0.000000e+00
Fitness 5.000000e-04 9.970229e+18 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 (15000 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 (15000 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 (15000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.9365  0.0000  0.0635 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000     Inf 14.7398
Neutral  0.0000          0.0000
Fitness  0.0678     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 (15000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.7159  0.0002  0.2839 

Bayes factors:
          Dayhoff   Neutral   Fitness
Dayhoff    1.0000 3579.6667    2.5221
Neutral    0.0003    1.0000    0.0007
Fitness    0.3965 1419.3333    1.0000


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

Bayes factors:
             Dayhoff      Neutral      Fitness
Dayhoff 1.000000e+00 8.438338e+35 6.553462e+11
Neutral 0.000000e+00 1.000000e+00 0.000000e+00
Fitness 0.000000e+00 1.287615e+24 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 (15000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.9581  0.0000  0.0419 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000     Inf 22.8474
Neutral  0.0000          0.0000
Fitness  0.0438     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 (15000 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 (15000 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 14999.0000
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 (15000 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 (15000 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 (15000 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 (15000 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 (15000 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 (15000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.2569  0.4010  0.3421 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.6407  0.7511
Neutral  1.5607  1.0000  1.1723
Fitness  1.3313  0.8530  1.0000


Posterior model probabilities (mnlogistic):
Dayhoff Neutral Fitness 
 0.3382  0.0902  0.5716 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  3.7487  0.5917
Neutral  0.2668  1.0000  0.1579
Fitness  1.6899  6.3351  1.0000




Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (15000 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 (15000 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 (15000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.9897  0.0000  0.0103 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000     Inf 96.4026
Neutral  0.0000          0.0000
Fitness  0.0104     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 (15000 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 (15000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.4446  0.1667  0.3887 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  2.6665  1.1439
Neutral  0.3750  1.0000  0.4290
Fitness  0.8742  2.3311  1.0000


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

Bayes factors:
             Dayhoff      Neutral      Fitness
Dayhoff 1.000000e+00 9.284461e+69 2.780186e+13
Neutral 0.000000e+00 1.000000e+00 0.000000e+00
Fitness 0.000000e+00 3.339511e+56 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 (15000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.2143  0.1325  0.6532 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  1.6167  0.3280
Neutral  0.6185  1.0000  0.2029
Fitness  3.0485  4.9286  1.0000


Posterior model probabilities (mnlogistic):
Dayhoff Neutral Fitness 
 0.8985  0.0000  0.1015 

Bayes factors:
             Dayhoff      Neutral      Fitness
Dayhoff 1.000000e+00 1.936723e+22 8.847600e+00
Neutral 0.000000e+00 1.000000e+00 0.000000e+00
Fitness 1.130000e-01 2.188980e+21 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 (15000 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 (15000 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 (15000 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 (15000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.7909  0.0010  0.2081 

Bayes factors:
         Dayhoff  Neutral  Fitness
Dayhoff   1.0000 790.9333   3.8013
Neutral   0.0013   1.0000   0.0048
Fitness   0.2631 208.0667   1.0000


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

Bayes factors:
             Dayhoff      Neutral      Fitness
Dayhoff 1.000000e+00 4.138089e+41 6.878383e+05
Neutral 0.000000e+00 1.000000e+00 0.000000e+00
Fitness 0.000000e+00 6.016077e+35 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 (15000 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 (15000 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 14999.0000
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 (15000 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 (15000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.2415  0.3869  0.3716 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.6243  0.6500
Neutral  1.6017  1.0000  1.0411
Fitness  1.5385  0.9605  1.0000


Posterior model probabilities (mnlogistic):
Dayhoff Neutral Fitness 
 0.0383  0.0083  0.9533 

Bayes factors:
         Dayhoff  Neutral  Fitness
Dayhoff   1.0000   4.5950   0.0402
Neutral   0.2176   1.0000   0.0088
Fitness  24.8583 114.2244   1.0000




Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (15000 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 (15000 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 (15000 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 (15000 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 (15000 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 (15000 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 (15000 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 (15000 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 (15000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.2576  0.3963  0.3461 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.6500  0.7444
Neutral  1.5386  1.0000  1.1453
Fitness  1.3434  0.8732  1.0000


Posterior model probabilities (mnlogistic):
Dayhoff Neutral Fitness 
 0.3117  0.2595  0.4288 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  1.2015  0.7270
Neutral  0.8323  1.0000  0.6050
Fitness  1.3755  1.6528  1.0000




Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (15000 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 (15000 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 (15000 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 (15000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.4669  0.0093  0.5239 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000 50.3813  0.8912
Neutral  0.0198  1.0000  0.0177
Fitness  1.1221 56.5324  1.0000


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

Bayes factors:
             Dayhoff      Neutral      Fitness
Dayhoff 1.000000e+00 4.356507e+37 4.980045e+04
Neutral 0.000000e+00 1.000000e+00 0.000000e+00
Fitness 0.000000e+00 8.747927e+32 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 (15000 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 (15000 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 (15000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
  0.833   0.000   0.167 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000     Inf  4.9880
Neutral  0.0000          0.0000
Fitness  0.2005     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 (15000 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 (15000 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 (15000 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 (15000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.9282  0.0000  0.0718 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000     Inf 12.9276
Neutral  0.0000          0.0000
Fitness  0.0774     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 (15000 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 (15000 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 (15000 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 (15000 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 (15000 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 (15000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.9991  0.0000  0.0009 

Bayes factors:
          Dayhoff   Neutral   Fitness
Dayhoff    1.0000       Inf 1070.4286
Neutral    0.0000              0.0000
Fitness    0.0009       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 (15000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.5269  0.0632  0.4099 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  8.3376  1.2856
Neutral  0.1199  1.0000  0.1542
Fitness  0.7778  6.4852  1.0000


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

Bayes factors:
             Dayhoff      Neutral      Fitness
Dayhoff 1.000000e+00 1.307223e+25 3.929847e+03
Neutral 0.000000e+00 1.000000e+00 0.000000e+00
Fitness 3.000000e-04 3.326398e+21 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 (15000 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 (15000 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 (15000 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 (15000 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 (15000 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 (15000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.9837  0.0000  0.0163 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000     Inf 60.4754
Neutral  0.0000          0.0000
Fitness  0.0165     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 (15000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.4545  0.1107  0.4347 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  4.1048  1.0455
Neutral  0.2436  1.0000  0.2547
Fitness  0.9564  3.9259  1.0000


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

Bayes factors:
             Dayhoff      Neutral      Fitness
Dayhoff 1.000000e+00 2.600401e+63 1.120513e+05
Neutral 0.000000e+00 1.000000e+00 0.000000e+00
Fitness 0.000000e+00 2.320723e+58 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 (15000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.9975  0.0001  0.0025 

Bayes factors:
           Dayhoff    Neutral    Fitness
Dayhoff     1.0000 14962.0000   404.3784
Neutral     0.0001     1.0000     0.0270
Fitness     0.0025    37.0000     1.0000


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

Bayes factors:
              Dayhoff       Neutral       Fitness
Dayhoff  1.000000e+00 1.376879e+172  7.432725e+36
Neutral  0.000000e+00  1.000000e+00  0.000000e+00
Fitness  0.000000e+00 1.852455e+135  1.000000e+00




