I'm using AIC for model selection, and would like to use a relative likelihood measure to quantify how many times a model with minimum AIC (AICmin) fits better than the alternative (with AICi).
For that, I'm using Burnham et al. (2011) formula, which is:
RL = exp ( 0.5 * ( AICmin - AICi ))
The expression is quite easy. However, I'm worried to miss something. In mi case, AICmin is negative (
AICmin = -239.10,
AICi = 210.43), which makes the difference term (AICmin - AICi) also negative, and thus a relative likelihood on the order of zero (
RL = 2.43e-98) and does not make sense.
In the original article I don't find any reference saying that the difference should be absolute, but if so, the ratio becomes too high (
RL = 4.11+97) to me to feel sure. Am I missing something? Thank you!