Calculate AICs for a list of models

Description

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).

Usage

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  calc_AIC_vals(LnL_vals, nparam_vals)

Arguments

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.

Details

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.

Value

AIC_vals A vector of AIC results.

Note

Go BEARS!

Author(s)

Nicholas J. Matzke matzke@berkeley.edu

References

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

Burnham_Anderson_2002

Matzke_2012_IBS

See Also

calc_AIC_column, calc_AICc_column

Examples

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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)

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