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      94       1       5
Neutral       0      98       2
Fitness       1       3      96


Mean model posterior probabilities (mnlogistic)

$tol0.01
        Dayhoff Neutral Fitness
Dayhoff  0.9446  0.0040  0.0515
Neutral  0.0013  0.9370  0.0617
Fitness  0.0425  0.0441  0.9133




Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.0157  0.9843 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.0159
Fitness     Inf 62.8298  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 (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.1600  0.4297  0.4103 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.3724  0.3899
Neutral  2.6854  1.0000  1.0471
Fitness  2.5646  0.9550  1.0000


Posterior model probabilities (mnlogistic):
Dayhoff Neutral Fitness 
 0.0411  0.0000  0.9589 

Bayes factors:
             Dayhoff      Neutral      Fitness
Dayhoff 1.000000e+00 1.983358e+06 4.290000e-02
Neutral 0.000000e+00 1.000000e+00 0.000000e+00
Fitness 2.332840e+01 4.626863e+07 1.000000e+00




Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.0253  0.9747 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.0260
Fitness     Inf 38.4737  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 (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
  0.000   0.037   0.963 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.0384
Fitness     Inf 26.0270  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 (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
  0.000   0.116   0.884 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.1312
Fitness     Inf  7.6207  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 (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
  0.000   0.003   0.997 

Bayes factors:
         Dayhoff  Neutral  Fitness
Dayhoff            0.0000   0.0000
Neutral      Inf   1.0000   0.0030
Fitness      Inf 332.3333   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 (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.0117  0.9883 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.0118
Fitness     Inf 84.7143  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 (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.0003  0.9997 

Bayes factors:
          Dayhoff   Neutral   Fitness
Dayhoff              0.0000    0.0000
Neutral       Inf    1.0000    0.0003
Fitness       Inf 2999.0000    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 (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0017  0.0000  0.9983 

Bayes factors:
         Dayhoff  Neutral  Fitness
Dayhoff   1.0000      Inf   0.0017
Neutral   0.0000            0.0000
Fitness 599.0000      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 (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

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

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.0680
Fitness     Inf 14.7068  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 (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.2767  0.3650  0.3583 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.7580  0.7721
Neutral  1.3193  1.0000  1.0186
Fitness  1.2952  0.9817  1.0000


Posterior model probabilities (mnlogistic):
Dayhoff Neutral Fitness 
 0.2226  0.0000  0.7774 

Bayes factors:
             Dayhoff      Neutral      Fitness
Dayhoff       1.0000 1540156.5322       0.2863
Neutral       0.0000       1.0000       0.0000
Fitness       3.4929 5379676.4747       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 (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.0543  0.9457 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.0575
Fitness     Inf 17.4049  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 (3000 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 (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.0017  0.9983 

Bayes factors:
         Dayhoff  Neutral  Fitness
Dayhoff            0.0000   0.0000
Neutral      Inf   1.0000   0.0017
Fitness      Inf 599.0000   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 (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.0503  0.9497 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.0530
Fitness     Inf 18.8675  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 (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
   0.00    0.08    0.92 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff           0.000   0.000
Neutral     Inf   1.000   0.087
Fitness     Inf  11.500   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 (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0067  0.3237  0.6697 

Bayes factors:
         Dayhoff  Neutral  Fitness
Dayhoff   1.0000   0.0206   0.0100
Neutral  48.5500   1.0000   0.4833
Fitness 100.4500   2.0690   1.0000


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

Bayes factors:
             Dayhoff      Neutral      Fitness
Dayhoff 1.000000e+00 2.005171e+03 0.000000e+00
Neutral 5.000000e-04 1.000000e+00 0.000000e+00
Fitness 3.188846e+04 6.394183e+07 1.000000e+00




Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.2207  0.3513  0.4280 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.6281  0.5156
Neutral  1.5921  1.0000  0.8209
Fitness  1.9396  1.2182  1.0000


Posterior model probabilities (mnlogistic):
Dayhoff Neutral Fitness 
 0.1149  0.0000  0.8851 

Bayes factors:
             Dayhoff      Neutral      Fitness
Dayhoff 1.000000e+00 1.331775e+21 1.299000e-01
Neutral 0.000000e+00 1.000000e+00 0.000000e+00
Fitness 7.699600e+00 1.025412e+22 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 (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0003  0.1567  0.8430 

Bayes factors:
          Dayhoff   Neutral   Fitness
Dayhoff    1.0000    0.0021    0.0004
Neutral  470.0000    1.0000    0.1858
Fitness 2529.0000    5.3809    1.0000


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

Bayes factors:
             Dayhoff      Neutral      Fitness
Dayhoff 1.000000e+00 2.100000e-03 0.000000e+00
Neutral 4.753737e+02 1.000000e+00 0.000000e+00
Fitness 1.807340e+19 3.801935e+16 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 (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
  0.007   0.423   0.570 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.0165  0.0123
Neutral 60.4286  1.0000  0.7421
Fitness 81.4286  1.3475  1.0000


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

Bayes factors:
             Dayhoff      Neutral      Fitness
Dayhoff       1.0000      63.6121       0.0000
Neutral       0.0157       1.0000       0.0000
Fitness   80749.4872 5136647.2153       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 (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.0017  0.9983 

Bayes factors:
         Dayhoff  Neutral  Fitness
Dayhoff            0.0000   0.0000
Neutral      Inf   1.0000   0.0017
Fitness      Inf 599.0000   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 (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0367  0.4460  0.5173 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.0822  0.0709
Neutral 12.1636  1.0000  0.8621
Fitness 14.1091  1.1599  1.0000


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

Bayes factors:
             Dayhoff      Neutral      Fitness
Dayhoff 1.000000e+00 1.888360e+01 0.000000e+00
Neutral 5.300000e-02 1.000000e+00 0.000000e+00
Fitness 3.310224e+06 6.250894e+07 1.000000e+00




Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.0003  0.9997 

Bayes factors:
          Dayhoff   Neutral   Fitness
Dayhoff              0.0000    0.0000
Neutral       Inf    1.0000    0.0003
Fitness       Inf 2999.0000    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 (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.2283  0.4150  0.3567 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.5502  0.6402
Neutral  1.8175  1.0000  1.1636
Fitness  1.5620  0.8594  1.0000


Posterior model probabilities (mnlogistic):
Dayhoff Neutral Fitness 
 0.1974  0.4308  0.3718 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.4583  0.5309
Neutral  2.1820  1.0000  1.1585
Fitness  1.8835  0.8632  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 (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.0023  0.9977 

Bayes factors:
         Dayhoff  Neutral  Fitness
Dayhoff            0.0000   0.0000
Neutral      Inf   1.0000   0.0023
Fitness      Inf 427.5714   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 (3000 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 (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.0097  0.9903 

Bayes factors:
         Dayhoff  Neutral  Fitness
Dayhoff            0.0000   0.0000
Neutral      Inf   1.0000   0.0098
Fitness      Inf 102.4483   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 (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.0883  0.9117 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.0969
Fitness     Inf 10.3208  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 (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.0387  0.9613 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.0402
Fitness     Inf 24.8621  1.0000





Model selection with abc - Real data
Call: 
postpr(target = FullRealmatrix[j, ], index = ModelsVector, sumstat = FullSSmatrix, 
    tol = ABC_Tolerance, method = ABC_Method)
Data:
 postpr.out$values (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0487  0.5460  0.4053 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.0891  0.1201
Neutral 11.2192  1.0000  1.3470
Fitness  8.3288  0.7424  1.0000


Posterior model probabilities (mnlogistic):
Dayhoff Neutral Fitness 
 0.0025  0.0000  0.9975 

Bayes factors:
           Dayhoff    Neutral    Fitness
Dayhoff     1.0000    81.7716     0.0025
Neutral     0.0122     1.0000     0.0000
Fitness   402.8484 32941.5768     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 (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.2550  0.3427  0.4023 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.7442  0.6338
Neutral  1.3438  1.0000  0.8517
Fitness  1.5778  1.1741  1.0000


Posterior model probabilities (mnlogistic):
Dayhoff Neutral Fitness 
 0.1571  0.0000  0.8429 

Bayes factors:
             Dayhoff      Neutral      Fitness
Dayhoff 1.000000e+00 1.097298e+15 1.863000e-01
Neutral 0.000000e+00 1.000000e+00 0.000000e+00
Fitness 5.366700e+00 5.888903e+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 (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.0223  0.9777 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.0228
Fitness     Inf 43.7761  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 (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.2563  0.3880  0.3557 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.6607  0.7207
Neutral  1.5137  1.0000  1.0909
Fitness  1.3875  0.9167  1.0000


Posterior model probabilities (mnlogistic):
Dayhoff Neutral Fitness 
 0.4393  0.0442  0.5165 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  9.9395  0.8505
Neutral  0.1006  1.0000  0.0856
Fitness  1.1758 11.6865  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 (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.2527  0.3947  0.3527 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.6402  0.7164
Neutral  1.5620  1.0000  1.1191
Fitness  1.3958  0.8936  1.0000


Posterior model probabilities (mnlogistic):
Dayhoff Neutral Fitness 
 0.2392  0.2304  0.5304 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  1.0381  0.4510
Neutral  0.9633  1.0000  0.4345
Fitness  2.2172  2.3016  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 (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.0443  0.9557 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.0464
Fitness     Inf 21.5564  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 (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
  0.000   0.296   0.704 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.4205
Fitness     Inf  2.3784  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 (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0043  0.3483  0.6473 

Bayes factors:
         Dayhoff  Neutral  Fitness
Dayhoff   1.0000   0.0124   0.0067
Neutral  80.3846   1.0000   0.5381
Fitness 149.3846   1.8584   1.0000


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

Bayes factors:
             Dayhoff      Neutral      Fitness
Dayhoff       1.0000     737.5830       0.0001
Neutral       0.0014       1.0000       0.0000
Fitness    7481.2727 5518059.4245       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 (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.0147  0.9853 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.0149
Fitness     Inf 67.1818  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 (3000 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 (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.0917  0.9083 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.1009
Fitness     Inf  9.9091  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 (3000 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 (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.0113  0.9887 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.0115
Fitness     Inf 87.2353  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 (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.0513  0.9487 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.0541
Fitness     Inf 18.4805  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 (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.0017  0.9983 

Bayes factors:
         Dayhoff  Neutral  Fitness
Dayhoff            0.0000   0.0000
Neutral      Inf   1.0000   0.0017
Fitness      Inf 599.0000   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 (3000 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 (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0010  0.1047  0.8943 

Bayes factors:
         Dayhoff  Neutral  Fitness
Dayhoff   1.0000   0.0096   0.0011
Neutral 104.6667   1.0000   0.1170
Fitness 894.3333   8.5446   1.0000


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

Bayes factors:
             Dayhoff      Neutral      Fitness
Dayhoff       1.0000     148.2198       0.0000
Neutral       0.0067       1.0000       0.0000
Fitness   57967.7469 8591968.2018       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 (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.0613  0.9387 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.0653
Fitness     Inf 15.3043  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 (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.3617  0.2037  0.4347 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  1.7758  0.8321
Neutral  0.5631  1.0000  0.4686
Fitness  1.2018  2.1342  1.0000


Posterior model probabilities (mnlogistic):
Dayhoff Neutral Fitness 
 0.5015  0.0000  0.4985 

Bayes factors:
             Dayhoff      Neutral      Fitness
Dayhoff 1.000000e+00 6.490522e+10 1.006000e+00
Neutral 0.000000e+00 1.000000e+00 0.000000e+00
Fitness 9.940000e-01 6.451789e+10 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 (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
  0.000   0.001   0.999 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff           0.000   0.000
Neutral     Inf   1.000   0.001
Fitness     Inf 999.000   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 (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
  0.000   0.001   0.999 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff           0.000   0.000
Neutral     Inf   1.000   0.001
Fitness     Inf 999.000   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 (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.2013  0.7987 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.2521
Fitness     Inf  3.9669  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 (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

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

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.0468
Fitness     Inf 21.3881  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 (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0010  0.0387  0.9603 

Bayes factors:
         Dayhoff  Neutral  Fitness
Dayhoff   1.0000   0.0259   0.0010
Neutral  38.6667   1.0000   0.0403
Fitness 960.3333  24.8362   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 1.508529e+31 1.000000e+00 0.000000e+00
Fitness 3.788326e+41 2.511272e+10 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 (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
  0.002   0.464   0.534 

Bayes factors:
         Dayhoff  Neutral  Fitness
Dayhoff   1.0000   0.0043   0.0037
Neutral 232.0000   1.0000   0.8689
Fitness 267.0000   1.1509   1.0000


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

Bayes factors:
            Dayhoff     Neutral     Fitness
Dayhoff      1.0000      0.0421      0.0000
Neutral     23.7613      1.0000      0.0001
Fitness 396390.0221  16682.1492      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 (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0027  0.3933  0.6040 

Bayes factors:
         Dayhoff  Neutral  Fitness
Dayhoff   1.0000   0.0068   0.0044
Neutral 147.5000   1.0000   0.6512
Fitness 226.5000   1.5356   1.0000


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

Bayes factors:
             Dayhoff      Neutral      Fitness
Dayhoff 1.000000e+00 4.758867e+06 0.000000e+00
Neutral 0.000000e+00 1.000000e+00 0.000000e+00
Fitness 3.236076e+05 1.540006e+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 (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0757  0.3030  0.6213 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.2497  0.1218
Neutral  4.0044  1.0000  0.4877
Fitness  8.2115  2.0506  1.0000


Posterior model probabilities (mnlogistic):
Dayhoff Neutral Fitness 
 0.0204  0.0000  0.9796 

Bayes factors:
             Dayhoff      Neutral      Fitness
Dayhoff 1.000000e+00 7.486253e+16 2.080000e-02
Neutral 0.000000e+00 1.000000e+00 0.000000e+00
Fitness 4.805790e+01 3.597737e+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 (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
  0.260   0.399   0.341 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.6516  0.7625
Neutral  1.5346  1.0000  1.1701
Fitness  1.3115  0.8546  1.0000


Posterior model probabilities (mnlogistic):
Dayhoff Neutral Fitness 
 0.3054  0.0000  0.6946 

Bayes factors:
            Dayhoff     Neutral     Fitness
Dayhoff      1.0000 396764.1192      0.4397
Neutral      0.0000      1.0000      0.0000
Fitness      2.2742 902328.1116      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 (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
  0.000   0.007   0.993 

Bayes factors:
         Dayhoff  Neutral  Fitness
Dayhoff            0.0000   0.0000
Neutral      Inf   1.0000   0.0070
Fitness      Inf 141.8571   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 (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

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

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.0142
Fitness     Inf 70.4286  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 (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.2597  0.3983  0.3420 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.6519  0.7593
Neutral  1.5340  1.0000  1.1647
Fitness  1.3171  0.8586  1.0000


Posterior model probabilities (mnlogistic):
Dayhoff Neutral Fitness 
 0.1371  0.0001  0.8628 

Bayes factors:
          Dayhoff   Neutral   Fitness
Dayhoff    1.0000 1135.6300    0.1589
Neutral    0.0009    1.0000    0.0001
Fitness    6.2939 7147.5789    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 (3000 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 (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
  0.000   0.009   0.991 

Bayes factors:
         Dayhoff  Neutral  Fitness
Dayhoff            0.0000   0.0000
Neutral      Inf   1.0000   0.0091
Fitness      Inf 110.1111   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 (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.2283  0.4147  0.3570 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.5506  0.6396
Neutral  1.8161  1.0000  1.1615
Fitness  1.5635  0.8609  1.0000


Posterior model probabilities (mnlogistic):
Dayhoff Neutral Fitness 
 0.1550  0.4306  0.4144 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.3599  0.3740
Neutral  2.7784  1.0000  1.0390
Fitness  2.6741  0.9625  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 (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.0003  0.9997 

Bayes factors:
          Dayhoff   Neutral   Fitness
Dayhoff              0.0000    0.0000
Neutral       Inf    1.0000    0.0003
Fitness       Inf 2999.0000    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 (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.0517  0.9483 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.0545
Fitness     Inf 18.3548  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 (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.1243  0.2907  0.5850 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.4278  0.2125
Neutral  2.3378  1.0000  0.4969
Fitness  4.7051  2.0126  1.0000


Posterior model probabilities (mnlogistic):
Dayhoff Neutral Fitness 
 0.0050  0.0012  0.9938 

Bayes factors:
         Dayhoff  Neutral  Fitness
Dayhoff   1.0000   4.1587   0.0050
Neutral   0.2405   1.0000   0.0012
Fitness 199.0793 827.9050   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 (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0007  0.0517  0.9477 

Bayes factors:
          Dayhoff   Neutral   Fitness
Dayhoff    1.0000    0.0129    0.0007
Neutral   77.5000    1.0000    0.0545
Fitness 1421.5000   18.3419    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 9.104574e+71 1.000000e+00 0.000000e+00
Fitness 3.395920e+83 3.729906e+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 (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.2237  0.4340  0.3423 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.5154  0.6534
Neutral  1.9404  1.0000  1.2678
Fitness  1.5306  0.7888  1.0000


Posterior model probabilities (mnlogistic):
Dayhoff Neutral Fitness 
 0.0620  0.0013  0.9367 

Bayes factors:
         Dayhoff  Neutral  Fitness
Dayhoff   1.0000  46.6073   0.0662
Neutral   0.0215   1.0000   0.0014
Fitness  15.1115 704.3086   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 (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
  0.029   0.190   0.781 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.1526  0.0371
Neutral  6.5517  1.0000  0.2433
Fitness 26.9310  4.1105  1.0000


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

Bayes factors:
             Dayhoff      Neutral      Fitness
Dayhoff 1.000000e+00 1.259370e+06 0.000000e+00
Neutral 0.000000e+00 1.000000e+00 0.000000e+00
Fitness 2.162571e+04 2.723477e+10 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 (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
  0.000   0.019   0.981 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.0194
Fitness     Inf 51.6316  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 (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
  0.260   0.261   0.479 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.9962  0.5428
Neutral  1.0038  1.0000  0.5449
Fitness  1.8423  1.8352  1.0000


Posterior model probabilities (mnlogistic):
Dayhoff Neutral Fitness 
 0.1312  0.0000  0.8688 

Bayes factors:
             Dayhoff      Neutral      Fitness
Dayhoff 1.000000e+00 5.858895e+09 1.510000e-01
Neutral 0.000000e+00 1.000000e+00 0.000000e+00
Fitness 6.621100e+00 3.879232e+10 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 (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.1280  0.4197  0.4523 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.3050  0.2830
Neutral  3.2786  1.0000  0.9278
Fitness  3.5339  1.0778  1.0000


Posterior model probabilities (mnlogistic):
Dayhoff Neutral Fitness 
 0.0505  0.0000  0.9495 

Bayes factors:
            Dayhoff     Neutral     Fitness
Dayhoff      1.0000  26698.6801      0.0532
Neutral      0.0000      1.0000      0.0000
Fitness     18.8073 502129.8535      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 (3000 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 (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.1707  0.8293 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.2058
Fitness     Inf  4.8594  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 (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.0587  0.9413 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.0623
Fitness     Inf 16.0455  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 (3000 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 (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0010  0.0017  0.9973 

Bayes factors:
         Dayhoff  Neutral  Fitness
Dayhoff   1.0000   0.6000   0.0010
Neutral   1.6667   1.0000   0.0017
Fitness 997.3333 598.4000   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 1.098922e+05 1.000000e+00 0.000000e+00
Fitness 1.108330e+17 1.008562e+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 (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
  0.000   0.001   0.999 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff           0.000   0.000
Neutral     Inf   1.000   0.001
Fitness     Inf 999.000   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 (3000 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 (3000 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 (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
  0.000   0.242   0.758 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.3193
Fitness     Inf  3.1322  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 (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

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

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.0468
Fitness     Inf 21.3881  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 (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.1033  0.8967 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.1152
Fitness     Inf  8.6774  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 (3000 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 (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
  0.000   0.065   0.935 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.0695
Fitness     Inf 14.3846  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 (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.4013  0.1470  0.4517 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  2.7302  0.8886
Neutral  0.3663  1.0000  0.3255
Fitness  1.1254  3.0726  1.0000


Posterior model probabilities (mnlogistic):
Dayhoff Neutral Fitness 
  0.325   0.000   0.675 

Bayes factors:
             Dayhoff      Neutral      Fitness
Dayhoff 1.000000e+00 4.906118e+09 4.814000e-01
Neutral 0.000000e+00 1.000000e+00 0.000000e+00
Fitness 2.077300e+00 1.019131e+10 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 (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.0057  0.9943 

Bayes factors:
         Dayhoff  Neutral  Fitness
Dayhoff            0.0000   0.0000
Neutral      Inf   1.0000   0.0057
Fitness      Inf 175.4706   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 (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
  0.067   0.107   0.826 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.6262  0.0811
Neutral  1.5970  1.0000  0.1295
Fitness 12.3284  7.7196  1.0000


Posterior model probabilities (mnlogistic):
Dayhoff Neutral Fitness 
 0.0038  0.0000  0.9962 

Bayes factors:
             Dayhoff      Neutral      Fitness
Dayhoff 1.000000e+00 1.128353e+06 3.800000e-03
Neutral 0.000000e+00 1.000000e+00 0.000000e+00
Fitness 2.623294e+02 2.960002e+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 (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0797  0.4733  0.4470 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.1683  0.1782
Neutral  5.9414  1.0000  1.0589
Fitness  5.6109  0.9444  1.0000


Posterior model probabilities (mnlogistic):
Dayhoff Neutral Fitness 
  0.007   0.000   0.993 

Bayes factors:
             Dayhoff      Neutral      Fitness
Dayhoff 1.000000e+00 1.016512e+06 7.000000e-03
Neutral 0.000000e+00 1.000000e+00 0.000000e+00
Fitness 1.423720e+02 1.447228e+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 (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.0663  0.9337 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.0710
Fitness     Inf 14.0754  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 (3000 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 (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.0793  0.9207 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.0862
Fitness     Inf 11.6050  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 (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.2470  0.3973  0.3557 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.6216  0.6945
Neutral  1.6086  1.0000  1.1172
Fitness  1.4399  0.8951  1.0000


Posterior model probabilities (mnlogistic):
Dayhoff Neutral Fitness 
 0.2484  0.1788  0.5729 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  1.3894  0.4335
Neutral  0.7197  1.0000  0.3120
Fitness  2.3066  3.2048  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 (3000 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 (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.0097  0.9903 

Bayes factors:
         Dayhoff  Neutral  Fitness
Dayhoff            0.0000   0.0000
Neutral      Inf   1.0000   0.0098
Fitness      Inf 102.4483   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 (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0007  0.2233  0.7760 

Bayes factors:
          Dayhoff   Neutral   Fitness
Dayhoff    1.0000    0.0030    0.0009
Neutral  335.0000    1.0000    0.2878
Fitness 1164.0000    3.4746    1.0000


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

Bayes factors:
             Dayhoff      Neutral      Fitness
Dayhoff 1.000000e+00 7.295004e+05 0.000000e+00
Neutral 0.000000e+00 1.000000e+00 0.000000e+00
Fitness 4.075228e+04 2.972880e+10 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 (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.0077  0.9923 

Bayes factors:
         Dayhoff  Neutral  Fitness
Dayhoff            0.0000   0.0000
Neutral      Inf   1.0000   0.0077
Fitness      Inf 129.4348   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 (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.0063  0.9937 

Bayes factors:
         Dayhoff  Neutral  Fitness
Dayhoff            0.0000   0.0000
Neutral      Inf   1.0000   0.0064
Fitness      Inf 156.8947   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 (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0323  0.3580  0.6097 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.0903  0.0530
Neutral 11.0722  1.0000  0.5872
Fitness 18.8557  1.7030  1.0000


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

Bayes factors:
             Dayhoff      Neutral      Fitness
Dayhoff 1.000000e+00 4.840356e+06 1.000000e-04
Neutral 0.000000e+00 1.000000e+00 0.000000e+00
Fitness 1.140171e+04 5.518834e+10 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 (3000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0097  0.0470  0.9433 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.2057  0.0102
Neutral  4.8621  1.0000  0.0498
Fitness 97.5862 20.0709  1.0000


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

Bayes factors:
             Dayhoff      Neutral      Fitness
Dayhoff 1.000000e+00 8.350078e+06 0.000000e+00
Neutral 0.000000e+00 1.000000e+00 0.000000e+00
Fitness 9.316187e+04 7.779089e+11 1.000000e+00




