bootWeights | R Documentation |

Computes model weights using bootstrap.

```
bootWeights(object, ..., R, rank = c("AICc", "AIC", "BIC"))
```

`object, ...` |
two or more fitted |

`R` |
the number of replicates. |

`rank` |
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.

`Weights`

, `model.avg`

Other model weights:
`BGWeights()`

,
`cos2Weights()`

,
`jackknifeWeights()`

,
`stackingWeights()`

```
# 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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