# AICweights: Calculates AICc-weights for each model of a set of models In blmeco: Data Files and Functions Accompanying the Book "Bayesian Data Analysis in Ecology using R, BUGS and Stan"

## Description

Calculates AICc-weights for each model of a set of models

## Usage

 `1` ```AICweights(models) ```

## Arguments

 `models` a vector of characters with the model names

## Details

The AICc for small sample sizes is used (can also be applied for large samples)

## Value

a vector of model weights

## Note

The function uses the function AICc from the package MuMIn.

F. Korner

## References

Burnham, KP and Anderson DR (2002) Model selection and multimodel inference, a practical information-theoretic approach. Springer, New York

## Examples

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15``` ```data(periparusater) dat<-periparusater # preparation of the data dat\$age[dat\$age==0] <- NA # replace 0 with NA dat\$age[dat\$age==5] <- 4 # replace "after hatching year" with "non-hatching year" dat\$age <- factor(dat\$age) # 3 = hatching year, 4 = non hatching year dat\$sex[dat\$sex==0] <- NA # replace 0 by missing values dat\$sex <- factor(dat\$sex) # 1 = males, 2 = females # retain only those data where sex and age is not missing dat <- dat[complete.cases(dat\$sex, dat\$age),] mod1 <- lm(wing~sex+age, data=dat) mod2 <- lm(wing~sex*age, data=dat) AICweights(c("mod1", "mod2")) ```

blmeco documentation built on May 29, 2017, 6:45 p.m.