AICc: AICc
In BMhyd: PCM for Hybridization

Description Usage Arguments Details Value Author(s) References Examples

Calculates the second order Akaike's information criterion score for models of interest.

1 2	AICc(n, k,LogLik)

`n`	number of taxa for the given phylogenetic tree. It represents the sample size(the number of species on the tip of phylogeny).
`k`	number of free parameters in the model
`LogLik`	the minimum of the negative log-likelihood value obtained by optitimizing the likelihood function.

'AICc' is a function to compute the AICc values and is valid to select among different models. AICc = 2*n*k/(n-k-1) -2 log L where L is the maximum likelihood for the model.

The AICc values.

Dwueng-Chwuan Jhwueng

Burnham, K.P., and D.R. Anderson. 2004. Model selection and inference: a practical information-theoretic approach. Sec. Ed. Springer, New York.

    #assign the size 
	n<-5
	#assign the number of parameter
	k<-3
	#assign the negative log likelihood value.
	LogLik<- -2
	#compute the AICc score
	AICc(n,k,LogLik)
	# result AICc value of 26.