A list of AICs (Akaike Information Criterion) is calculated from two input lists. Lower values of AIC indicate some combination of better fit to the data and more parsimony in the model (fewer free parameters).
A vector of log-likelihoods (typically negative, but may not be for continuous data).
A vector of the number of parameters for each model.
The two input lists are:
1. A list of data likelihoods under a variety of
2. A list of the number of free parameters under each model.
See Burnham et al. (2002) and http://www.brianomeara.info/tutorials/aic for discussion of AIC and its uses.
data.frame column of
Nicholas J. Matzke [email protected]
1 2 3 4 5
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.