IC weights quantify the evidence in favor of different models in a set. This function normalizes the IC values to obtain IC weights, which sum to 1. The model with the highest weight is most supported by the data. The ratio of different weights gives the relative support in favor of one model over another.
ic_weights(x, ...)An object for which a method exists.
Additional arguments.
A list of class ic_weights with elements $weights, which
contains the model weights, and $comparison, which contains the relative
support in favor of each model over the others.
Wagenmakers, E. J., & Farrell, S. (2004). AIC model selection using Akaike weights. Psychonomic bulletin & review, 11(1), 192-196. doi:10.3758/BF03206482
ics <- c(100, 200, 102, 300)
ic_weights(ics)
#> $weights
#> Model 1 Model 2 Model 3 Model 4
#> 7.310586e-01 1.410029e-22 2.689414e-01 2.719593e-44
#>
#> $comparison
#> Model 1 Model 2 Model 3 Model 4
#> Model 1 1.000000e+00 5.184706e+21 2.718282e+00 2.688117e+43
#> Model 2 1.928750e-22 1.000000e+00 5.242886e-22 5.184706e+21
#> Model 3 3.678794e-01 1.907347e+21 1.000000e+00 9.889030e+42
#> Model 4 3.720076e-44 1.928750e-22 1.011221e-43 1.000000e+00
#>
#> attr(,"class")
#> [1] "ic_weights" "list"