Computes model weights using bootstrap.
bootWeights(object, ..., R, rank = c("AICc", "AIC", "BIC"))
two or more fitted
the number of replicates.
a character string, specifying the information criterion to use
for model ranking. Defaults to
The models are fitted repeatedly to a resampled data set and ranked using AIC-type criterion. The model weights represent the proportion of replicates when a model has the lowest IC value.
A numeric vector of model weights.
Kamil Bartoń, Carsten Dormann
Dormann, C. et al. (2018) Model averaging in ecology: a review of Bayesian, information-theoretic, and tactical approaches for predictive inference. Ecological Monographs, 88, 485–504.
Other model weights:
# To speed up the bootstrap, use 'x = TRUE' so that model matrix is included # in the returned object fm <- glm(Prop ~ mortality + dose, family = binomial, data = Beetle, na.action = na.fail, x = TRUE) fml <- lapply(dredge(fm, eval = FALSE), eval) am <- model.avg(fml) Weights(am) <- bootWeights(am, data = Beetle, R = 25) summary(am)
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