IC {paleoTS} | R Documentation |
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.
IC(w, logL = NULL, K = NULL, n = NULL, meth = c("AICc", "AIC", "BIC")) akaike.wts(aa)
w |
output from an optimization such as opt.GRW |
logL |
log-likelihood |
K |
the number of free parameters |
n |
sample size for AICc and BIC calculations (= the number of evolutionary transisitons) |
meth |
which information criterion to compute; one of AIC, AICc, or BIC |
aa |
vector of AIC or AICc values used to compute Akaike weights |
~~ If necessary, more details than the description above ~~
the computed information criterion, or a vector of Akaike weights
Gene Hunt
Hunt, G. 2006. Fitting and comparing models of phyletic evolution: random walks and beyond. Paleobiology32:578–601.
x <- sim.GRW(ns=40, ms=0.1, vs=0.1) m1<- opt.GRW(x) m2<- opt.URW(x) m3<- opt.Stasis(x) akaike.wts(c(m1$AICc, m2$AICc, m3$AICc)) # note easier to use fit3models()