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

$tol0.01
        Dayhoff Neutral Fitness
Dayhoff      98       0       2
Neutral       0      98       2
Fitness       3       1      96


Mean model posterior probabilities (mnlogistic)

$tol0.01
        Dayhoff Neutral Fitness
Dayhoff  0.9718  0.0000  0.0282
Neutral  0.0026  0.9552  0.0422
Fitness  0.0550  0.0419  0.9031




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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
  0.000   0.016   0.984 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.0163
Fitness     Inf 61.5000  1.0000





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.1647  0.4280  0.4073 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.3847  0.4043
Neutral  2.5992  1.0000  1.0507
Fitness  2.4737  0.9517  1.0000


Posterior model probabilities (mnlogistic):
Dayhoff Neutral Fitness 
 0.0464  0.0000  0.9536 

Bayes factors:
             Dayhoff      Neutral      Fitness
Dayhoff 1.000000e+00 2.599748e+07 4.870000e-02
Neutral 0.000000e+00 1.000000e+00 0.000000e+00
Fitness 2.054410e+01 5.340942e+08 1.000000e+00




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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.0287  0.9713 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.0295
Fitness     Inf 33.8837  1.0000





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

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

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





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
  0.000   0.118   0.882 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.1338
Fitness     Inf  7.4746  1.0000





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

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

Bayes factors:
         Dayhoff  Neutral  Fitness
Dayhoff            0.0000   0.0000
Neutral      Inf   1.0000   0.0033
Fitness      Inf 299.0000   1.0000





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.0073  0.9927 

Bayes factors:
         Dayhoff  Neutral  Fitness
Dayhoff            0.0000   0.0000
Neutral      Inf   1.0000   0.0074
Fitness      Inf 135.3636   1.0000





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

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

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





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

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

Bayes factors:
         Dayhoff  Neutral  Fitness
Dayhoff   1.0000      Inf   0.0013
Neutral   0.0000            0.0000
Fitness 749.0000      Inf   1.0000





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.0687  0.9313 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.0737
Fitness     Inf 13.5631  1.0000





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.2813  0.3473  0.3713 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.8100  0.7576
Neutral  1.2346  1.0000  0.9354
Fitness  1.3199  1.0691  1.0000


Posterior model probabilities (mnlogistic):
Dayhoff Neutral Fitness 
 0.2389  0.0000  0.7611 

Bayes factors:
             Dayhoff      Neutral      Fitness
Dayhoff 1.000000e+00 4.788501e+07 3.140000e-01
Neutral 0.000000e+00 1.000000e+00 0.000000e+00
Fitness 3.185000e+00 1.525161e+08 1.000000e+00




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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.0567  0.9433 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.0601
Fitness     Inf 16.6471  1.0000





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

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

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





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

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

Bayes factors:
         Dayhoff  Neutral  Fitness
Dayhoff            0.0000   0.0000
Neutral      Inf   1.0000   0.0013
Fitness      Inf 749.0000   1.0000





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.0433  0.9567 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.0453
Fitness     Inf 22.0769  1.0000





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.0867  0.9133 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.0949
Fitness     Inf 10.5385  1.0000





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0060  0.2913  0.7027 

Bayes factors:
         Dayhoff  Neutral  Fitness
Dayhoff   1.0000   0.0206   0.0085
Neutral  48.5556   1.0000   0.4146
Fitness 117.1111   2.4119   1.0000


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

Bayes factors:
             Dayhoff      Neutral      Fitness
Dayhoff 1.000000e+00 6.642173e+02 0.000000e+00
Neutral 1.500000e-03 1.000000e+00 0.000000e+00
Fitness 1.078780e+09 7.165441e+11 1.000000e+00




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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.2140  0.3413  0.4447 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.6270  0.4813
Neutral  1.5950  1.0000  0.7676
Fitness  2.0779  1.3027  1.0000


Posterior model probabilities (mnlogistic):
Dayhoff Neutral Fitness 
 0.0887  0.0000  0.9113 

Bayes factors:
             Dayhoff      Neutral      Fitness
Dayhoff 1.000000e+00 4.974614e+12 9.740000e-02
Neutral 0.000000e+00 1.000000e+00 0.000000e+00
Fitness 1.026830e+01 5.108101e+13 1.000000e+00




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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0007  0.1273  0.8720 

Bayes factors:
          Dayhoff   Neutral   Fitness
Dayhoff    1.0000    0.0052    0.0008
Neutral  191.0000    1.0000    0.1460
Fitness 1308.0000    6.8482    1.0000


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

Bayes factors:
             Dayhoff      Neutral      Fitness
Dayhoff 1.000000e+00 1.997100e+00 0.000000e+00
Neutral 5.007000e-01 1.000000e+00 0.000000e+00
Fitness 1.918628e+14 3.831756e+14 1.000000e+00




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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0067  0.4627  0.5307 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.0144  0.0126
Neutral 69.4000  1.0000  0.8719
Fitness 79.6000  1.1470  1.0000


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

Bayes factors:
            Dayhoff     Neutral     Fitness
Dayhoff      1.0000     12.3609      0.0001
Neutral      0.0809      1.0000      0.0000
Fitness  16310.5891 201613.6347      1.0000




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

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

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





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0307  0.4433  0.5260 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.0692  0.0583
Neutral 14.4565  1.0000  0.8428
Fitness 17.1522  1.1865  1.0000


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

Bayes factors:
             Dayhoff      Neutral      Fitness
Dayhoff 1.000000e+00 2.000000e-04 0.000000e+00
Neutral 5.855104e+03 1.000000e+00 0.000000e+00
Fitness 5.949459e+08 1.016115e+05 1.000000e+00




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

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

Bayes factors:
          Dayhoff   Neutral   Fitness
Dayhoff              0.0000    0.0000
Neutral       Inf    1.0000    0.0007
Fitness       Inf 1499.0000    1.0000





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.2200  0.4013  0.3787 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.5482  0.5810
Neutral  1.8242  1.0000  1.0599
Fitness  1.7212  0.9435  1.0000


Posterior model probabilities (mnlogistic):
Dayhoff Neutral Fitness 
 0.2277  0.3934  0.3789 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.5788  0.6010
Neutral  1.7276  1.0000  1.0382
Fitness  1.6639  0.9632  1.0000




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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
  0.000   0.002   0.998 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff           0.000   0.000
Neutral     Inf   1.000   0.002
Fitness     Inf 499.000   1.000





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

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

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





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

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

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.0101
Fitness     Inf 99.0000  1.0000





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
  0.000   0.084   0.916 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.0917
Fitness     Inf 10.9048  1.0000





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
  0.000   0.034   0.966 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.0352
Fitness     Inf 28.4118  1.0000





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0453  0.5433  0.4113 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.0834  0.1102
Neutral 11.9853  1.0000  1.3209
Fitness  9.0735  0.7571  1.0000


Posterior model probabilities (mnlogistic):
Dayhoff Neutral Fitness 
 0.0020  0.0003  0.9977 

Bayes factors:
          Dayhoff   Neutral   Fitness
Dayhoff    1.0000    6.5117    0.0020
Neutral    0.1536    1.0000    0.0003
Fitness  501.9711 3268.7074    1.0000




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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.2640  0.3247  0.4113 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.8131  0.6418
Neutral  1.2298  1.0000  0.7893
Fitness  1.5581  1.2669  1.0000


Posterior model probabilities (mnlogistic):
Dayhoff Neutral Fitness 
 0.1579  0.0000  0.8421 

Bayes factors:
             Dayhoff      Neutral      Fitness
Dayhoff 1.000000e+00 1.198869e+09 1.875000e-01
Neutral 0.000000e+00 1.000000e+00 0.000000e+00
Fitness 5.333300e+00 6.393928e+09 1.000000e+00




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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.0193  0.9807 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.0197
Fitness     Inf 50.7241  1.0000





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.2593  0.3807  0.3600 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.6813  0.7204
Neutral  1.4679  1.0000  1.0574
Fitness  1.3882  0.9457  1.0000


Posterior model probabilities (mnlogistic):
Dayhoff Neutral Fitness 
 0.4359  0.0431  0.5211 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000 10.1171  0.8365
Neutral  0.0988  1.0000  0.0827
Fitness  1.1954 12.0943  1.0000




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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
  0.260   0.384   0.356 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.6771  0.7303
Neutral  1.4769  1.0000  1.0787
Fitness  1.3692  0.9271  1.0000


Posterior model probabilities (mnlogistic):
Dayhoff Neutral Fitness 
 0.2446  0.2206  0.5348 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  1.1090  0.4574
Neutral  0.9017  1.0000  0.4124
Fitness  2.1865  2.4248  1.0000




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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
   0.00    0.04    0.96 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.0417
Fitness     Inf 24.0000  1.0000





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.2927  0.7073 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.4138
Fitness     Inf  2.4169  1.0000





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0033  0.3700  0.6267 

Bayes factors:
         Dayhoff  Neutral  Fitness
Dayhoff   1.0000   0.0090   0.0053
Neutral 111.0000   1.0000   0.5904
Fitness 188.0000   1.6937   1.0000


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

Bayes factors:
            Dayhoff     Neutral     Fitness
Dayhoff      1.0000      0.9343      0.0000
Neutral      1.0703      1.0000      0.0000
Fitness 312450.2801 291928.4951      1.0000




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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
  0.000   0.016   0.984 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.0163
Fitness     Inf 61.5000  1.0000





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
  0.000   0.004   0.996 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff           0.000   0.000
Neutral     Inf   1.000   0.004
Fitness     Inf 249.000   1.000





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
  0.000   0.092   0.908 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.1013
Fitness     Inf  9.8696  1.0000





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
  0.000   0.006   0.994 

Bayes factors:
         Dayhoff  Neutral  Fitness
Dayhoff            0.0000   0.0000
Neutral      Inf   1.0000   0.0060
Fitness      Inf 165.6667   1.0000





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.0133  0.9867 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.0135
Fitness     Inf 74.0000  1.0000





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
  0.000   0.052   0.948 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.0549
Fitness     Inf 18.2308  1.0000





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

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

Bayes factors:
         Dayhoff  Neutral  Fitness
Dayhoff            0.0000   0.0000
Neutral      Inf   1.0000   0.0013
Fitness      Inf 749.0000   1.0000





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

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

Bayes factors:
         Dayhoff  Neutral  Fitness
Dayhoff            0.0000   0.0000
Neutral      Inf   1.0000   0.0033
Fitness      Inf 299.0000   1.0000





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0013  0.0793  0.9193 

Bayes factors:
         Dayhoff  Neutral  Fitness
Dayhoff   1.0000   0.0168   0.0015
Neutral  59.5000   1.0000   0.0863
Fitness 689.5000  11.5882   1.0000


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

Bayes factors:
             Dayhoff      Neutral      Fitness
Dayhoff       1.0000       2.3104       0.0000
Neutral       0.4328       1.0000       0.0000
Fitness 2144036.6621 4953687.9774       1.0000




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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
  0.000   0.052   0.948 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.0549
Fitness     Inf 18.2308  1.0000





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.3587  0.2040  0.4373 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  1.7582  0.8201
Neutral  0.5688  1.0000  0.4665
Fitness  1.2193  2.1438  1.0000


Posterior model probabilities (mnlogistic):
Dayhoff Neutral Fitness 
 0.4914  0.0000  0.5086 

Bayes factors:
             Dayhoff      Neutral      Fitness
Dayhoff 1.000000e+00 1.167236e+18 9.660000e-01
Neutral 0.000000e+00 1.000000e+00 0.000000e+00
Fitness 1.035200e+00 1.208296e+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 (1500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

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

Bayes factors:
          Dayhoff   Neutral   Fitness
Dayhoff              0.0000    0.0000
Neutral       Inf    1.0000    0.0007
Fitness       Inf 1499.0000    1.0000





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
  0.000   0.002   0.998 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff           0.000   0.000
Neutral     Inf   1.000   0.002
Fitness     Inf 499.000   1.000





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.2027  0.7973 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.2542
Fitness     Inf  3.9342  1.0000





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.0327  0.9673 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.0338
Fitness     Inf 29.6122  1.0000





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

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

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





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0007  0.4800  0.5193 

Bayes factors:
         Dayhoff  Neutral  Fitness
Dayhoff   1.0000   0.0014   0.0013
Neutral 720.0000   1.0000   0.9243
Fitness 779.0000   1.0819   1.0000


Posterior model probabilities (mnlogistic):
Dayhoff Neutral Fitness 
 0.0000  0.0009  0.9991 

Bayes factors:
             Dayhoff      Neutral      Fitness
Dayhoff 1.000000e+00 0.000000e+00 0.000000e+00
Neutral 9.637769e+11 1.000000e+00 9.000000e-04
Fitness 1.039429e+15 1.078495e+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 (1500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0013  0.4240  0.5747 

Bayes factors:
         Dayhoff  Neutral  Fitness
Dayhoff   1.0000   0.0031   0.0023
Neutral 318.0000   1.0000   0.7378
Fitness 431.0000   1.3553   1.0000


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

Bayes factors:
             Dayhoff      Neutral      Fitness
Dayhoff 1.000000e+00 0.000000e+00 0.000000e+00
Neutral 8.675261e+31 1.000000e+00 0.000000e+00
Fitness 8.654206e+49 9.975731e+17 1.000000e+00




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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0753  0.2953  0.6293 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.2551  0.1197
Neutral  3.9204  1.0000  0.4693
Fitness  8.3540  2.1309  1.0000


Posterior model probabilities (mnlogistic):
Dayhoff Neutral Fitness 
 0.0169  0.0000  0.9831 

Bayes factors:
             Dayhoff      Neutral      Fitness
Dayhoff 1.000000e+00 1.146741e+13 1.720000e-02
Neutral 0.000000e+00 1.000000e+00 0.000000e+00
Fitness 5.814390e+01 6.667602e+14 1.000000e+00




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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.2527  0.3833  0.3640 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.6591  0.6941
Neutral  1.5172  1.0000  1.0531
Fitness  1.4406  0.9496  1.0000


Posterior model probabilities (mnlogistic):
Dayhoff Neutral Fitness 
 0.2518  0.0000  0.7482 

Bayes factors:
             Dayhoff      Neutral      Fitness
Dayhoff       1.0000 2140496.1418       0.3366
Neutral       0.0000       1.0000       0.0000
Fitness       2.9711 6359620.1578       1.0000




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

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

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





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.0127  0.9873 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.0128
Fitness     Inf 77.9474  1.0000





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.2547  0.3767  0.3687 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.6761  0.6908
Neutral  1.4791  1.0000  1.0217
Fitness  1.4476  0.9788  1.0000


Posterior model probabilities (mnlogistic):
Dayhoff Neutral Fitness 
 0.1283  0.0001  0.8717 

Bayes factors:
           Dayhoff    Neutral    Fitness
Dayhoff     1.0000  2082.2353     0.1472
Neutral     0.0005     1.0000     0.0001
Fitness     6.7945 14147.8498     1.0000




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

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

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





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.0067  0.9933 

Bayes factors:
         Dayhoff  Neutral  Fitness
Dayhoff            0.0000   0.0000
Neutral      Inf   1.0000   0.0067
Fitness      Inf 149.0000   1.0000





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.2207  0.4013  0.3780 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.5498  0.5838
Neutral  1.8187  1.0000  1.0617
Fitness  1.7130  0.9419  1.0000


Posterior model probabilities (mnlogistic):
Dayhoff Neutral Fitness 
 0.1660  0.3997  0.4343 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.4153  0.3822
Neutral  2.4077  1.0000  0.9203
Fitness  2.6162  1.0866  1.0000




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

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

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





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
  0.000   0.044   0.956 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.0460
Fitness     Inf 21.7273  1.0000





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.1247  0.2853  0.5900 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.4369  0.2113
Neutral  2.2888  1.0000  0.4836
Fitness  4.7326  2.0678  1.0000


Posterior model probabilities (mnlogistic):
Dayhoff Neutral Fitness 
 0.0069  0.0001  0.9931 

Bayes factors:
           Dayhoff    Neutral    Fitness
Dayhoff     1.0000   105.6486     0.0069
Neutral     0.0095     1.0000     0.0001
Fitness   144.6797 15285.2080     1.0000




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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0013  0.0427  0.9560 

Bayes factors:
         Dayhoff  Neutral  Fitness
Dayhoff   1.0000   0.0312   0.0014
Neutral  32.0000   1.0000   0.0446
Fitness 717.0000  22.4062   1.0000


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

Bayes factors:
             Dayhoff      Neutral      Fitness
Dayhoff 1.000000e+00 0.000000e+00 0.000000e+00
Neutral 8.984315e+04 1.000000e+00 0.000000e+00
Fitness 3.444518e+17 3.833923e+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 (1500 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.2140  0.4407  0.3453 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.4856  0.6197
Neutral  2.0592  1.0000  1.2761
Fitness  1.6137  0.7837  1.0000


Posterior model probabilities (mnlogistic):
Dayhoff Neutral Fitness 
 0.0735  0.0006  0.9259 

Bayes factors:
          Dayhoff   Neutral   Fitness
Dayhoff    1.0000  122.8601    0.0794
Neutral    0.0081    1.0000    0.0006
Fitness   12.5962 1547.5748    1.0000




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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0267  0.1667  0.8067 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.1600  0.0331
Neutral  6.2500  1.0000  0.2066
Fitness 30.2500  4.8400  1.0000


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

Bayes factors:
             Dayhoff      Neutral      Fitness
Dayhoff 1.000000e+00 3.452845e+03 0.000000e+00
Neutral 3.000000e-04 1.000000e+00 0.000000e+00
Fitness 1.139873e+05 3.935804e+08 1.000000e+00




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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
   0.00    0.02    0.98 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.0204
Fitness     Inf 49.0000  1.0000





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.2533  0.2673  0.4793 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.9476  0.5285
Neutral  1.0553  1.0000  0.5577
Fitness  1.8921  1.7930  1.0000


Posterior model probabilities (mnlogistic):
Dayhoff Neutral Fitness 
 0.1093  0.0000  0.8907 

Bayes factors:
             Dayhoff      Neutral      Fitness
Dayhoff 1.000000e+00 1.411272e+08 1.227000e-01
Neutral 0.000000e+00 1.000000e+00 0.000000e+00
Fitness 8.153000e+00 1.150617e+09 1.000000e+00




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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.1333  0.4087  0.4580 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.3263  0.2911
Neutral  3.0650  1.0000  0.8923
Fitness  3.4350  1.1207  1.0000


Posterior model probabilities (mnlogistic):
Dayhoff Neutral Fitness 
 0.0584  0.0000  0.9415 

Bayes factors:
           Dayhoff    Neutral    Fitness
Dayhoff     1.0000  1965.9477     0.0621
Neutral     0.0005     1.0000     0.0000
Fitness    16.1145 31680.2720     1.0000




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

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

Bayes factors:
          Dayhoff   Neutral   Fitness
Dayhoff              0.0000    0.0000
Neutral       Inf    1.0000    0.0007
Fitness       Inf 1499.0000    1.0000





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

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

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.2285
Fitness     Inf  4.3763  1.0000





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
  0.000   0.062   0.938 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.0661
Fitness     Inf 15.1290  1.0000





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

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

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





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0007  0.0013  0.9980 

Bayes factors:
          Dayhoff   Neutral   Fitness
Dayhoff    1.0000    0.5000    0.0007
Neutral    2.0000    1.0000    0.0013
Fitness 1497.0000  748.5000    1.0000


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

Bayes factors:
             Dayhoff      Neutral      Fitness
Dayhoff 1.000000e+00 0.000000e+00 0.000000e+00
Neutral 2.008063e+12 1.000000e+00 0.000000e+00
Fitness 3.231104e+27 1.609066e+15 1.000000e+00




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

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

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





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.0087  0.9913 

Bayes factors:
         Dayhoff  Neutral  Fitness
Dayhoff            0.0000   0.0000
Neutral      Inf   1.0000   0.0087
Fitness      Inf 114.3846   1.0000





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.0367  0.9633 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.0381
Fitness     Inf 26.2727  1.0000





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.2633  0.7367 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.3575
Fitness     Inf  2.7975  1.0000





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.0633  0.9367 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.0676
Fitness     Inf 14.7895  1.0000





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.0993  0.9007 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.1103
Fitness     Inf  9.0671  1.0000





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

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

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





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
  0.000   0.082   0.918 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.0893
Fitness     Inf 11.1951  1.0000





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
  0.412   0.138   0.450 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  2.9855  0.9156
Neutral  0.3350  1.0000  0.3067
Fitness  1.0922  3.2609  1.0000


Posterior model probabilities (mnlogistic):
Dayhoff Neutral Fitness 
 0.3476  0.0000  0.6524 

Bayes factors:
             Dayhoff      Neutral      Fitness
Dayhoff 1.000000e+00 5.981185e+14 5.329000e-01
Neutral 0.000000e+00 1.000000e+00 0.000000e+00
Fitness 1.876600e+00 1.122412e+15 1.000000e+00




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

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

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





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0567  0.1107  0.8327 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.5120  0.0681
Neutral  1.9529  1.0000  0.1329
Fitness 14.6941  7.5241  1.0000


Posterior model probabilities (mnlogistic):
Dayhoff Neutral Fitness 
 0.0011  0.0000  0.9989 

Bayes factors:
             Dayhoff      Neutral      Fitness
Dayhoff 1.000000e+00 3.647591e+16 1.100000e-03
Neutral 0.000000e+00 1.000000e+00 0.000000e+00
Fitness 8.883765e+02 3.240434e+19 1.000000e+00




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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0840  0.4673  0.4487 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.1797  0.1872
Neutral  5.5635  1.0000  1.0416
Fitness  5.3413  0.9601  1.0000


Posterior model probabilities (mnlogistic):
Dayhoff Neutral Fitness 
 0.0063  0.0000  0.9937 

Bayes factors:
             Dayhoff      Neutral      Fitness
Dayhoff 1.000000e+00 1.266498e+06 6.400000e-03
Neutral 0.000000e+00 1.000000e+00 0.000000e+00
Fitness 1.566912e+02 1.984491e+08 1.000000e+00




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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.0827  0.9173 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.0901
Fitness     Inf 11.0968  1.0000





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.0067  0.9933 

Bayes factors:
         Dayhoff  Neutral  Fitness
Dayhoff            0.0000   0.0000
Neutral      Inf   1.0000   0.0067
Fitness      Inf 149.0000   1.0000





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.0653  0.9347 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.0699
Fitness     Inf 14.3061  1.0000





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.2480  0.3813  0.3707 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.6503  0.6691
Neutral  1.5376  1.0000  1.0288
Fitness  1.4946  0.9720  1.0000


Posterior model probabilities (mnlogistic):
Dayhoff Neutral Fitness 
 0.2348  0.1567  0.6085 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  1.4984  0.3859
Neutral  0.6674  1.0000  0.2576
Fitness  2.5911  3.8824  1.0000




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

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

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





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

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

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.0101
Fitness     Inf 99.0000  1.0000





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
  0.000   0.224   0.776 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.2887
Fitness     Inf  3.4643  1.0000





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.0093  0.9907 

Bayes factors:
         Dayhoff  Neutral  Fitness
Dayhoff            0.0000   0.0000
Neutral      Inf   1.0000   0.0094
Fitness      Inf 106.1429   1.0000





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.0073  0.9927 

Bayes factors:
         Dayhoff  Neutral  Fitness
Dayhoff            0.0000   0.0000
Neutral      Inf   1.0000   0.0074
Fitness      Inf 135.3636   1.0000





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0373  0.3733  0.5893 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.1000  0.0633
Neutral 10.0000  1.0000  0.6335
Fitness 15.7857  1.5786  1.0000


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

Bayes factors:
             Dayhoff      Neutral      Fitness
Dayhoff 1.000000e+00 6.324724e+07 1.000000e-04
Neutral 0.000000e+00 1.000000e+00 0.000000e+00
Fitness 1.431841e+04 9.056000e+11 1.000000e+00




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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0073  0.0340  0.9587 

Bayes factors:
         Dayhoff  Neutral  Fitness
Dayhoff   1.0000   0.2157   0.0076
Neutral   4.6364   1.0000   0.0355
Fitness 130.7273  28.1961   1.0000


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

Bayes factors:
             Dayhoff      Neutral      Fitness
Dayhoff 1.000000e+00 4.822272e+08 0.000000e+00
Neutral 0.000000e+00 1.000000e+00 0.000000e+00
Fitness 7.686491e+04 3.706635e+13 1.000000e+00




