paleoTS (version 0.4-4)

IC: Compute information criterion scores and Akaike weights for evoltuionary models

Description

These functions compute information criteria (IC) or Akaike weights based on information scores (akaike.wts). Function IC is used internally by the optimization functions and generally will not need to be called directly by the user.

Usage

IC(logL, K, n = NULL, method = c("AICc", "AIC", "BIC"))
akaike.wts(aa)

Arguments

logL

log-likelihood

K

the number of free parameters

n

sample size for AICc and BIC calculations

method

which information criterion to compute; one of AIC, AICc, or BIC

aa

vector of AIC or AICc values used to compute Akaike weights

Value

• the computed information criterion, or a vector of Akaike weights

Details

These functions are used by the functions as.paleoTSfit and compareModels, and will rarely need to be used directly by the user.

References

Hunt, G. 2006. Fitting and comparing models of phyletic evolution: random walks and beyond. Paleobiology 32:578--601.

See Also

opt.GRW, compareModels, as.paleoTSfit

Examples

x <- sim.GRW(ns=40, ms=0.1, vs=0.1)
 m1<- opt.GRW(x)	
 m2<- opt.URW(x)
 aw<- akaike.wts(c(m1$AICc, m2$AIC))  # easier to use compareModels(m1,m2)