Compute model weights according to the information criterion scores of each
model.
Usage
ic.wghts(scores)
Arguments
scores
The information criterion scores.
Value
A vector of weights, which can be interpreted (loosely) as the
relative desireability of the models corresponding to the weights
Details
The formula is quite simple: Identify the smallest (best) score among the
various models. Subtract this minimum value from all of the scores, and
call the resulting set of scores $s$. Compute exp(-0.5 s) for all the
scores, and normalize the resulting vector to obtain the vector of model
weights