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BioGeoBEARS (version 0.2.1)

getAICc: Calculate AICc

Description

Calculate AICc (Akaike Information Criterion). Lower values of AICc indicate some combination of better fit to the data and more parsimony in the model (fewer free parameters).

Usage

getAICc(LnL, numparams, samplesize)

Arguments

LnL
The log-likelihood (typically negative, but may not be for continuous data).
numparams
The number of parameters for each model.
samplesize
The number of data on which the model conferred likelihood.

Value

AICcval A vector of AICc results.

Details

See Burnham et al. (2002) and http://www.brianomeara.info/tutorials/AICc for discussion of AICc and its uses.

References

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

Burnham_Anderson_2002

Matzke_2012_IBS

See Also

calc_AICc_column, calc_AICc_column

Examples

Run this code
LnL = -34.5
numparams = 2
samplesize = 20
getAICc(LnL, numparams, samplesize)

LnL = -20.9
numparams = 3
samplesize = 20
getAICc(LnL, numparams, samplesize)

LnL = -34.5
numparams = 2
samplesize = 5
getAICc(LnL, numparams, samplesize)

LnL = -20.9
numparams = 3
samplesize = 5
getAICc(LnL, numparams, samplesize)

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