AkaikeWeight: Akaike weight
In BMhyd: PCM for Hybridization

Description Usage Arguments Details Value Author(s) References Examples

Calculate Akaike weight for the models

1 2	AkaikeWeight(Delta.AICc.Array)

Delta.AICc.Array

Delta.AICc.Array is defined as the difference between the AICc value and the minimum AICc value among candidate models.

For n models of interest, the Akaikei weight for the i th model is defined as w = exp(-0.5* Δ AICc_i)/ sum_i dAICc_i where Δ AICc_i is the difference of the AICc value between the the i th model and the best model. The weights can be used in model averaging in advanced.

Akaike weights.

Dwueng-Chwuan Jhwueng

Burham, K.P., Anderson, D.R. (2002) Model selection and multimodel inference: a practical information-theoretic approach. Second edition. Springer. New York.

	#simulate 4 AICc values for 4 models.
	AICc_Array<-rnorm(4, mean=10,sd=1)
	#calculate the delta AICc
	Delta.AICc.Array<-AICc_Array-min(AICc_Array)
	#calculate the Akaike weight
	AkaikeWeight(Delta.AICc.Array)