calc_AIC_vals: Calculate AICs for a list of models
In BioGeoBEARS: BioGeography with Bayesian (and Likelihood) Evolutionary Analysis in R Scripts

Description Usage Arguments Details Value Note Author(s) References See Also Examples

View source: R/BioGeoBEARS_generics_v1.R

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).

1	calc_AIC_vals(LnL_vals, nparam_vals)

`LnL_vals`	A vector of log-likelihoods (typically negative, but may not be for continuous data).
`nparam_vals`	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 models.
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.

AIC_vals A vector of AIC results.

Go BEARS!

Nicholas J. Matzke matzke@berkeley.edu

http://phylo.wikidot.com/matzke-2013-international-biogeography-society-poster http://www.brianomeara.info/tutorials/aic

Burnham_Anderson_2002

Matzke_2012_IBS

calc_AIC_column, calc_AICc_column

LnL_vals = c(-34.5, -20.9)
nparam_vals = c(2, 3)
calc_AIC_vals(LnL_vals, nparam_vals)

LnL_vals = c(-20.9, -20.9, -20.9, -20.9)
nparam_vals = c(3, 4, 5, 6)
calc_AIC_vals(LnL_vals, nparam_vals)