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

$tol0.05
        Dayhoff Neutral Fitness
Dayhoff      98       0       2
Neutral       0      97       3
Fitness       1       3      96


Mean model posterior probabilities (mnlogistic)

$tol0.05
        Dayhoff Neutral Fitness
Dayhoff  0.9629  0.0022  0.0348
Neutral  0.0057  0.8835  0.1108
Fitness  0.0222  0.1021  0.8757




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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.0828  0.9172 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.0903
Fitness     Inf 11.0773  1.0000





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.2471  0.3955  0.3574 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.6249  0.6915
Neutral  1.6002  1.0000  1.1065
Fitness  1.4462  0.9037  1.0000


Posterior model probabilities (mnlogistic):
Dayhoff Neutral Fitness 
 0.0463  0.0003  0.9533 

Bayes factors:
          Dayhoff   Neutral   Fitness
Dayhoff    1.0000  143.1521    0.0486
Neutral    0.0070    1.0000    0.0003
Fitness   20.5713 2944.8231    1.0000




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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.0888  0.9112 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.0975
Fitness     Inf 10.2613  1.0000





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.1184  0.8816 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.1343
Fitness     Inf  7.4459  1.0000





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.3623  0.6377 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.5681
Fitness     Inf  1.7604  1.0000





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.1348  0.8652 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.1558
Fitness     Inf  6.4184  1.0000





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.0979  0.9021 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.1086
Fitness     Inf  9.2110  1.0000





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.0323  0.9677 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.0333
Fitness     Inf 29.9917  1.0000





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0127  0.0892  0.8981 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.1428  0.0142
Neutral  7.0052  1.0000  0.0993
Fitness 70.5288 10.0680  1.0000


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

Bayes factors:
            Dayhoff     Neutral     Fitness
Dayhoff           1       37385           0
Neutral           0           1           0
Fitness     1324678 49523096211           1




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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0011  0.3157  0.6832 

Bayes factors:
         Dayhoff  Neutral  Fitness
Dayhoff   1.0000   0.0034   0.0016
Neutral 296.0000   1.0000   0.4621
Fitness 640.5000   2.1639   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 4.290139e+04 1.000000e+00 0.000000e+00
Fitness 1.556299e+11 3.627619e+06 1.000000e+00




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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.2698  0.3919  0.3383 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.6885  0.7974
Neutral  1.4524  1.0000  1.1582
Fitness  1.2540  0.8634  1.0000


Posterior model probabilities (mnlogistic):
Dayhoff Neutral Fitness 
 0.2395  0.0001  0.7604 

Bayes factors:
          Dayhoff   Neutral   Fitness
Dayhoff    1.0000 1987.1832    0.3149
Neutral    0.0005    1.0000    0.0002
Fitness    3.1754 6310.0562    1.0000




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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.2146  0.7854 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.2732
Fitness     Inf  3.6598  1.0000





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.0915  0.9085 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.1007
Fitness     Inf  9.9329  1.0000





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.0165  0.9835 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.0168
Fitness     Inf 59.4839  1.0000





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.1959  0.8041 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.2437
Fitness     Inf  4.1038  1.0000





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.3367  0.6633 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.5077
Fitness     Inf  1.9697  1.0000





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0256  0.4929  0.4815 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.0519  0.0532
Neutral 19.2526  1.0000  1.0235
Fitness 18.8099  0.9770  1.0000


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

Bayes factors:
             Dayhoff      Neutral      Fitness
Dayhoff       1.0000    1201.5097       0.0002
Neutral       0.0008       1.0000       0.0000
Fitness    6123.8315 7357842.6054       1.0000




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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.2555  0.3813  0.3632 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.6699  0.7034
Neutral  1.4927  1.0000  1.0499
Fitness  1.4217  0.9524  1.0000


Posterior model probabilities (mnlogistic):
Dayhoff Neutral Fitness 
 0.1148  0.0000  0.8852 

Bayes factors:
             Dayhoff      Neutral      Fitness
Dayhoff 1.000000e+00 1.014664e+07 1.297000e-01
Neutral 0.000000e+00 1.000000e+00 0.000000e+00
Fitness 7.708300e+00 7.821338e+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 (15000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0132  0.4374  0.5494 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.0302  0.0240
Neutral 33.1364  1.0000  0.7961
Fitness 41.6212  1.2561  1.0000


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

Bayes factors:
             Dayhoff      Neutral      Fitness
Dayhoff       1.0000       3.3084       0.0000
Neutral       0.3023       1.0000       0.0000
Fitness  303563.4079 1004306.2854       1.0000




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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0553  0.4854  0.4593 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.1140  0.1205
Neutral  8.7723  1.0000  1.0569
Fitness  8.3000  0.9462  1.0000


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

Bayes factors:
            Dayhoff     Neutral     Fitness
Dayhoff      1.0000     32.7402      0.0001
Neutral      0.0305      1.0000      0.0000
Fitness  12131.8336 397198.1318      1.0000




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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.0529  0.9471 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.0559
Fitness     Inf 17.8917  1.0000





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.1111  0.4744  0.4145 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.2343  0.2681
Neutral  4.2687  1.0000  1.1446
Fitness  3.7295  0.8737  1.0000


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

Bayes factors:
             Dayhoff      Neutral      Fitness
Dayhoff       1.0000    2909.1381       0.0006
Neutral       0.0003       1.0000       0.0000
Fitness    1733.8393 5043977.7846       1.0000




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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.0362  0.9638 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.0376
Fitness     Inf 26.6243  1.0000





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.2569  0.4011  0.3420 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.6404  0.7511
Neutral  1.5616  1.0000  1.1729
Fitness  1.3314  0.8526  1.0000


Posterior model probabilities (mnlogistic):
Dayhoff Neutral Fitness 
 0.1592  0.5273  0.3136 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.3019  0.5075
Neutral  3.3128  1.0000  1.6814
Fitness  1.9703  0.5947  1.0000




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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.0229  0.9771 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.0235
Fitness     Inf 42.6047  1.0000





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.0203  0.9797 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.0208
Fitness     Inf 48.1803  1.0000





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0005  0.0698  0.9297 

Bayes factors:
          Dayhoff   Neutral   Fitness
Dayhoff    1.0000    0.0076    0.0006
Neutral  130.8750    1.0000    0.0751
Fitness 1743.1250   13.3190    1.0000


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

Bayes factors:
             Dayhoff      Neutral      Fitness
Dayhoff 1.000000e+00 4.459500e+00 0.000000e+00
Neutral 2.242000e-01 1.000000e+00 0.000000e+00
Fitness 1.449318e+08 6.463222e+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 (15000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.3923  0.6077 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.6456
Fitness     Inf  1.5489  1.0000





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0025  0.3587  0.6388 

Bayes factors:
         Dayhoff  Neutral  Fitness
Dayhoff   1.0000   0.0071   0.0040
Neutral 141.5789   1.0000   0.5615
Fitness 252.1579   1.7810   1.0000


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

Bayes factors:
             Dayhoff      Neutral      Fitness
Dayhoff 1.000000e+00 9.700000e-03 0.000000e+00
Neutral 1.029585e+02 1.000000e+00 0.000000e+00
Fitness 1.627125e+10 1.580370e+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 (15000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.1765  0.4416  0.3819 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.3996  0.4620
Neutral  2.5025  1.0000  1.1562
Fitness  2.1643  0.8649  1.0000


Posterior model probabilities (mnlogistic):
Dayhoff Neutral Fitness 
 0.0054  0.0000  0.9945 

Bayes factors:
           Dayhoff    Neutral    Fitness
Dayhoff     1.0000   179.0674     0.0055
Neutral     0.0056     1.0000     0.0000
Fitness   182.7010 32715.7919     1.0000




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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.2419  0.3779  0.3802 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.6400  0.6362
Neutral  1.5626  1.0000  0.9940
Fitness  1.5719  1.0060  1.0000


Posterior model probabilities (mnlogistic):
Dayhoff Neutral Fitness 
 0.1698  0.0000  0.8302 

Bayes factors:
             Dayhoff      Neutral      Fitness
Dayhoff       1.0000  552332.6726       0.2045
Neutral       0.0000       1.0000       0.0000
Fitness       4.8902 2701000.4719       1.0000




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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.2195  0.7805 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.2812
Fitness     Inf  3.5565  1.0000





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.2623  0.3967  0.3410 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.6611  0.7691
Neutral  1.5127  1.0000  1.1634
Fitness  1.3002  0.8595  1.0000


Posterior model probabilities (mnlogistic):
Dayhoff Neutral Fitness 
 0.4129  0.0327  0.5544 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000 12.6243  0.7447
Neutral  0.0792  1.0000  0.0590
Fitness  1.3428 16.9520  1.0000




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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.2607  0.3981  0.3412 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.6550  0.7642
Neutral  1.5267  1.0000  1.1667
Fitness  1.3086  0.8571  1.0000


Posterior model probabilities (mnlogistic):
Dayhoff Neutral Fitness 
 0.2320  0.1821  0.5859 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  1.2736  0.3959
Neutral  0.7852  1.0000  0.3108
Fitness  2.5259  3.2171  1.0000




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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.2491  0.7509 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.3318
Fitness     Inf  3.0139  1.0000





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0037  0.4283  0.5680 

Bayes factors:
         Dayhoff  Neutral  Fitness
Dayhoff   1.0000   0.0087   0.0066
Neutral 114.7143   1.0000   0.7540
Fitness 152.1429   1.3263   1.0000


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

Bayes factors:
             Dayhoff      Neutral      Fitness
Dayhoff         1.00         0.00         0.00
Neutral     33003.93         1.00         0.00
Fitness 883222470.79     26761.13         1.00




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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0391  0.4589  0.5020 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.0851  0.0778
Neutral 11.7474  1.0000  0.9142
Fitness 12.8498  1.0938  1.0000


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

Bayes factors:
             Dayhoff      Neutral      Fitness
Dayhoff 1.000000e+00 1.924491e+03 1.000000e-04
Neutral 5.000000e-04 1.000000e+00 0.000000e+00
Fitness 9.783248e+03 1.882777e+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 (15000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.1652  0.8348 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.1979
Fitness     Inf  5.0533  1.0000





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.1096  0.8904 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.1231
Fitness     Inf  8.1241  1.0000





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0001  0.2797  0.7202 

Bayes factors:
          Dayhoff   Neutral   Fitness
Dayhoff    1.0000    0.0005    0.0002
Neutral 2097.5000    1.0000    0.3883
Fitness 5401.5000    2.5752    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 3.048349e+27 1.000000e+00 0.000000e+00
Fitness 6.028153e+35 1.977514e+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 (15000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.0549  0.9451 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.0581
Fitness     Inf 17.2260  1.0000





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
  0.000   0.247   0.753 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.3280
Fitness     Inf  3.0486  1.0000





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0013  0.2803  0.7184 

Bayes factors:
         Dayhoff  Neutral  Fitness
Dayhoff   1.0000   0.0048   0.0019
Neutral 210.2000   1.0000   0.3901
Fitness 538.8000   2.5633   1.0000


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

Bayes factors:
             Dayhoff      Neutral      Fitness
Dayhoff 1.000000e+00 1.620000e-02 0.000000e+00
Neutral 6.160520e+01 1.000000e+00 0.000000e+00
Fitness 1.998664e+07 3.244312e+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 (15000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0005  0.1653  0.8342 

Bayes factors:
          Dayhoff   Neutral   Fitness
Dayhoff    1.0000    0.0032    0.0006
Neutral  309.8750    1.0000    0.1981
Fitness 1564.1250    5.0476    1.0000


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

Bayes factors:
             Dayhoff      Neutral      Fitness
Dayhoff 1.000000e+00 9.962000e+00 0.000000e+00
Neutral 1.004000e-01 1.000000e+00 0.000000e+00
Fitness 9.826890e+06 9.789576e+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 (15000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.1303  0.8697 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.1499
Fitness     Inf  6.6726  1.0000





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0067  0.3783  0.6149 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.0178  0.0109
Neutral 56.1881  1.0000  0.6152
Fitness 91.3267  1.6254  1.0000


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

Bayes factors:
            Dayhoff     Neutral     Fitness
Dayhoff       1.000       1.441       0.000
Neutral       0.694       1.000       0.000
Fitness 2217782.738 3195882.224       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 (15000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.1554  0.8446 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff           0.000   0.000
Neutral     Inf   1.000   0.184
Fitness     Inf   5.435   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 (15000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.2745  0.3614  0.3641 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.7595  0.7538
Neutral  1.3167  1.0000  0.9925
Fitness  1.3267  1.0076  1.0000


Posterior model probabilities (mnlogistic):
Dayhoff Neutral Fitness 
 0.5147  0.0000  0.4853 

Bayes factors:
             Dayhoff      Neutral      Fitness
Dayhoff 1.000000e+00 3.552397e+07 1.060700e+00
Neutral 0.000000e+00 1.000000e+00 0.000000e+00
Fitness 9.427000e-01 3.349006e+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 (15000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.0784  0.9216 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.0851
Fitness     Inf 11.7551  1.0000





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.0191  0.9809 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.0194
Fitness     Inf 51.4476  1.0000





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.4167  0.5833 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.7145
Fitness     Inf  1.3996  1.0000





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.1763  0.8237 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.2141
Fitness     Inf  4.6711  1.0000





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0110  0.2661  0.7229 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.0413  0.0152
Neutral 24.1939  1.0000  0.3682
Fitness 65.7152  2.7162  1.0000


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

Bayes factors:
             Dayhoff      Neutral      Fitness
Dayhoff 1.000000e+00 1.546519e+02 0.000000e+00
Neutral 6.500000e-03 1.000000e+00 0.000000e+00
Fitness 1.207852e+07 1.867966e+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 (15000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0143  0.5139  0.4718 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.0278  0.0302
Neutral 36.0234  1.0000  1.0893
Fitness 33.0701  0.9180  1.0000


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

Bayes factors:
            Dayhoff     Neutral     Fitness
Dayhoff      1.0000      0.0243      0.0000
Neutral     41.1351      1.0000      0.0002
Fitness 205923.3259   5006.0218      1.0000




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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0215  0.4976  0.4809 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.0431  0.0446
Neutral 23.1801  1.0000  1.0347
Fitness 22.4037  0.9665  1.0000


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

Bayes factors:
            Dayhoff     Neutral     Fitness
Dayhoff 1.00000e+00 1.08740e+11 0.00000e+00
Neutral 0.00000e+00 1.00000e+00 0.00000e+00
Fitness 2.29816e+04 2.49902e+15 1.00000e+00




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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.1287  0.4418  0.4295 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.2912  0.2995
Neutral  3.4337  1.0000  1.0286
Fitness  3.3383  0.9722  1.0000


Posterior model probabilities (mnlogistic):
Dayhoff Neutral Fitness 
 0.0348  0.0000  0.9652 

Bayes factors:
             Dayhoff      Neutral      Fitness
Dayhoff 1.000000e+00 1.773549e+07 3.610000e-02
Neutral 0.000000e+00 1.000000e+00 0.000000e+00
Fitness 2.773420e+01 4.918793e+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 (15000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.2654  0.3945  0.3401 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.6727  0.7804
Neutral  1.4866  1.0000  1.1602
Fitness  1.2813  0.8619  1.0000


Posterior model probabilities (mnlogistic):
Dayhoff Neutral Fitness 
 0.3748  0.0012  0.6239 

Bayes factors:
         Dayhoff  Neutral  Fitness
Dayhoff   1.0000 307.1048   0.6008
Neutral   0.0033   1.0000   0.0020
Fitness   1.6645 511.1781   1.0000




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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  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 (15000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.1305  0.8695 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.1501
Fitness     Inf  6.6609  1.0000





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.2649  0.3939  0.3412 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.6726  0.7765
Neutral  1.4867  1.0000  1.1544
Fitness  1.2879  0.8663  1.0000


Posterior model probabilities (mnlogistic):
Dayhoff Neutral Fitness 
 0.1246  0.0024  0.8730 

Bayes factors:
         Dayhoff  Neutral  Fitness
Dayhoff   1.0000  52.5708   0.1427
Neutral   0.0190   1.0000   0.0027
Fitness   7.0056 368.2898   1.0000




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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.1641  0.8359 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.1963
Fitness     Inf  5.0951  1.0000





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.0369  0.9631 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.0383
Fitness     Inf 26.1248  1.0000





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.2567  0.4012  0.3421 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.6399  0.7505
Neutral  1.5627  1.0000  1.1729
Fitness  1.3324  0.8526  1.0000


Posterior model probabilities (mnlogistic):
Dayhoff Neutral Fitness 
 0.1229  0.5296  0.3475 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.2321  0.3536
Neutral  4.3092  1.0000  1.5238
Fitness  2.8279  0.6562  1.0000




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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.0217  0.9783 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.0221
Fitness     Inf 45.1538  1.0000





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.1447  0.8553 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.1692
Fitness     Inf  5.9093  1.0000





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.2029  0.3727  0.4243 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.5444  0.4782
Neutral  1.8367  1.0000  0.8784
Fitness  2.0910  1.1384  1.0000


Posterior model probabilities (mnlogistic):
Dayhoff Neutral Fitness 
 0.0037  0.0005  0.9958 

Bayes factors:
          Dayhoff   Neutral   Fitness
Dayhoff    1.0000    7.7727    0.0037
Neutral    0.1287    1.0000    0.0005
Fitness  267.8696 2082.0699    1.0000




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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0053  0.2741  0.7205 

Bayes factors:
         Dayhoff  Neutral  Fitness
Dayhoff   1.0000   0.0195   0.0074
Neutral  51.4000   1.0000   0.3805
Fitness 135.1000   2.6284   1.0000


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

Bayes factors:
             Dayhoff      Neutral      Fitness
Dayhoff 1.000000e+00 5.851000e-01 0.000000e+00
Neutral 1.709000e+00 1.000000e+00 0.000000e+00
Fitness 1.457837e+08 8.530307e+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 (15000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.2618  0.3974  0.3408 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.6588  0.7682
Neutral  1.5180  1.0000  1.1661
Fitness  1.3018  0.8576  1.0000


Posterior model probabilities (mnlogistic):
Dayhoff Neutral Fitness 
 0.0668  0.0137  0.9194 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  4.8626  0.0727
Neutral  0.2057  1.0000  0.0150
Fitness 13.7552 66.8854  1.0000




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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0679  0.4189  0.5133 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.1620  0.1322
Neutral  6.1719  1.0000  0.8161
Fitness  7.5629  1.2254  1.0000


Posterior model probabilities (mnlogistic):
Dayhoff Neutral Fitness 
 0.0001  0.0001  0.9998 

Bayes factors:
           Dayhoff    Neutral    Fitness
Dayhoff     1.0000     0.7183     0.0001
Neutral     1.3922     1.0000     0.0001
Fitness 14290.9384 10264.8442     1.0000




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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.1054  0.8946 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.1178
Fitness     Inf  8.4877  1.0000





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.2599  0.3698  0.3703 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.7029  0.7020
Neutral  1.4227  1.0000  0.9987
Fitness  1.4245  1.0013  1.0000


Posterior model probabilities (mnlogistic):
Dayhoff Neutral Fitness 
 0.1364  0.0000  0.8636 

Bayes factors:
             Dayhoff      Neutral      Fitness
Dayhoff 1.000000e+00 1.048444e+08 1.580000e-01
Neutral 0.000000e+00 1.000000e+00 0.000000e+00
Fitness 6.331000e+00 6.637690e+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 (15000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.2090  0.4122  0.3788 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.5070  0.5517
Neutral  1.9722  1.0000  1.0882
Fitness  1.8124  0.9190  1.0000


Posterior model probabilities (mnlogistic):
Dayhoff Neutral Fitness 
 0.1296  0.0000  0.8704 

Bayes factors:
             Dayhoff      Neutral      Fitness
Dayhoff 1.000000e+00 1.261170e+07 1.489000e-01
Neutral 0.000000e+00 1.000000e+00 0.000000e+00
Fitness 6.717000e+00 8.471215e+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 (15000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.0369  0.9631 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.0383
Fitness     Inf 26.1248  1.0000





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.4235  0.5765 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.7345
Fitness     Inf  1.3615  1.0000





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.1393  0.8607 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.1618
Fitness     Inf  6.1805  1.0000





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.0228  0.9772 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.0233
Fitness     Inf 42.8596  1.0000





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0078  0.1029  0.8893 

Bayes factors:
         Dayhoff  Neutral  Fitness
Dayhoff   1.0000   0.0758   0.0088
Neutral  13.1966   1.0000   0.1158
Fitness 114.0085   8.6392   1.0000


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

Bayes factors:
             Dayhoff      Neutral      Fitness
Dayhoff 1.000000e+00 8.080141e+02 0.000000e+00
Neutral 1.200000e-03 1.000000e+00 0.000000e+00
Fitness 3.393043e+06 2.741627e+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 (15000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
  0.000   0.027   0.973 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.0277
Fitness     Inf 36.0370  1.0000





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.0413  0.9587 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.0430
Fitness     Inf 23.2326  1.0000





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.3413  0.6587 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.5182
Fitness     Inf  1.9297  1.0000





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0047  0.4341  0.5611 

Bayes factors:
         Dayhoff  Neutral  Fitness
Dayhoff   1.0000   0.0109   0.0084
Neutral  91.7183   1.0000   0.7737
Fitness 118.5493   1.2925   1.0000


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

Bayes factors:
             Dayhoff      Neutral      Fitness
Dayhoff 1.000000e+00 4.781990e+01 0.000000e+00
Neutral 2.090000e-02 1.000000e+00 0.000000e+00
Fitness 4.879251e+07 2.333251e+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 (15000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.1599  0.8401 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.1904
Fitness     Inf  5.2526  1.0000





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0001  0.4100  0.5899 

Bayes factors:
          Dayhoff   Neutral   Fitness
Dayhoff    1.0000    0.0003    0.0002
Neutral 3075.0000    1.0000    0.6951
Fitness 4424.0000    1.4387    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 1.017979e+32 1.000000e+00 0.000000e+00
Fitness 1.132595e+37 1.112591e+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 (15000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.1678  0.8322 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.2016
Fitness     Inf  4.9595  1.0000





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.2236  0.7764 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.2880
Fitness     Inf  3.4723  1.0000





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.2804  0.3348  0.3848 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.8375  0.7287
Neutral  1.1940  1.0000  0.8701
Fitness  1.3723  1.1493  1.0000


Posterior model probabilities (mnlogistic):
Dayhoff Neutral Fitness 
 0.3061  0.0000  0.6939 

Bayes factors:
             Dayhoff      Neutral      Fitness
Dayhoff 1.000000e+00 6.708293e+06 4.412000e-01
Neutral 0.000000e+00 1.000000e+00 0.000000e+00
Fitness 2.266500e+00 1.520453e+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 (15000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.1453  0.8547 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.1700
Fitness     Inf  5.8839  1.0000





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.1109  0.3505  0.5386 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.3165  0.2060
Neutral  3.1593  1.0000  0.6507
Fitness  4.8552  1.5368  1.0000


Posterior model probabilities (mnlogistic):
Dayhoff Neutral Fitness 
 0.0047  0.0000  0.9953 

Bayes factors:
             Dayhoff      Neutral      Fitness
Dayhoff 1.000000e+00 4.694002e+06 4.700000e-03
Neutral 0.000000e+00 1.000000e+00 0.000000e+00
Fitness 2.105960e+02 9.885379e+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 (15000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.1723  0.4297  0.3981 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.4009  0.4328
Neutral  2.4942  1.0000  1.0794
Fitness  2.3108  0.9265  1.0000


Posterior model probabilities (mnlogistic):
Dayhoff Neutral Fitness 
 0.0098  0.0000  0.9902 

Bayes factors:
            Dayhoff     Neutral     Fitness
Dayhoff      1.0000   1429.5473      0.0099
Neutral      0.0007      1.0000      0.0000
Fitness    101.3287 144854.2426      1.0000




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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.1225  0.8775 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.1396
Fitness     Inf  7.1655  1.0000





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.0662  0.9338 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.0709
Fitness     Inf 14.1057  1.0000





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.3506  0.6494 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.5399
Fitness     Inf  1.8523  1.0000





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.2607  0.3985  0.3407 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.6542  0.7652
Neutral  1.5285  1.0000  1.1696
Fitness  1.3068  0.8550  1.0000


Posterior model probabilities (mnlogistic):
Dayhoff Neutral Fitness 
 0.2769  0.0793  0.6438 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  3.4909  0.4300
Neutral  0.2865  1.0000  0.1232
Fitness  2.3256  8.1183  1.0000




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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.0946  0.9054 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.1045
Fitness     Inf  9.5708  1.0000





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.0641  0.9359 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.0685
Fitness     Inf 14.5925  1.0000





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0033  0.4659  0.5308 

Bayes factors:
         Dayhoff  Neutral  Fitness
Dayhoff   1.0000   0.0070   0.0062
Neutral 142.6327   1.0000   0.8778
Fitness 162.4898   1.1392   1.0000


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

Bayes factors:
             Dayhoff      Neutral      Fitness
Dayhoff 1.000000e+00 2.266620e+01 0.000000e+00
Neutral 4.410000e-02 1.000000e+00 0.000000e+00
Fitness 2.020022e+06 4.578626e+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 (15000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.0476  0.9524 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.0500
Fitness     Inf 20.0084  1.0000





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0000  0.0428  0.9572 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff          0.0000  0.0000
Neutral     Inf  1.0000  0.0447
Fitness     Inf 22.3645  1.0000





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

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0962  0.4598  0.4440 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.2092  0.2167
Neutral  4.7796  1.0000  1.0356
Fitness  4.6154  0.9656  1.0000


Posterior model probabilities (mnlogistic):
Dayhoff Neutral Fitness 
 0.0004  0.0000  0.9996 

Bayes factors:
             Dayhoff      Neutral      Fitness
Dayhoff 1.000000e+00 1.451782e+07 4.000000e-04
Neutral 0.000000e+00 1.000000e+00 0.000000e+00
Fitness 2.836695e+03 4.118263e+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 (15000 posterior samples)
Models a priori:
 Dayhoff, Neutral, Fitness
Models a posteriori:
 Dayhoff, Neutral, Fitness

Proportion of accepted simulations (rejection):
Dayhoff Neutral Fitness 
 0.0298  0.3785  0.5917 

Bayes factors:
        Dayhoff Neutral Fitness
Dayhoff  1.0000  0.0787  0.0504
Neutral 12.7025  1.0000  0.6398
Fitness 19.8546  1.5631  1.0000


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

Bayes factors:
             Dayhoff      Neutral      Fitness
Dayhoff 1.000000e+00 5.434778e+04 5.000000e-04
Neutral 0.000000e+00 1.000000e+00 0.000000e+00
Fitness 1.928108e+03 1.047884e+08 1.000000e+00




