compare_AICw: Compare AIC weights for a set of models.
In hstojic/cogmod: Useful functions for cognitive modeling

Description Usage Arguments Value Examples

With AIC weights instead of raw AIC values one can get the sense of magnitude how much more likely (in terms of Kullback-Leibler discrepancy) one model is than some other model that has also been fitted. To get such a likelihood we divide the AIC weight of one model with the AIC weight of the other fitted model. See Wagenmakers and Farrel (2004) for details.

1	compare_AICw(AICweights, model_names = NA)

`AICweights`	A numeric vector of AIC weigths.
`model_names`	Optional character vector with names of the models.

A data frame where each cell represents a likelihood of the model denoted by the row name with respect to the model denoted by the cell's column name. Order of the models from the input to the function is preserved.

# example from Wagenmakers and Farrel (2004) article
AIC <- c(204, 202, 206, 206, 214)
AICweights <- AICw(AIC)$AICweights
# comparing AIC weights
compare_AICw(AICweights)