aic {ESTER} R Documentation

## Computes the Akaike Information Criterion

### Description

Computes the Akaike Information Criterion of a model. Except when the number of observations is much larger than the number of parameters (i.e., n / k > 40), we apply the second-order bias correction for small samples (AICc), as suggested by Burnham & Anderson (2002, 2004).

### Usage

aic(mod)


### Arguments

 mod A fitted model of class lm or merMod.

### References

Burnham, K. P., \& Anderson, D. R. (2002). Model Selection and Multimodel Inference: A Practical Information-Theoretical Approach. 2d ed. New York: Springer-Verlag.

Burnham, K. P., \& Anderson, D. R. (2004). Multimodel inference: Understanding AIC and BIC in model selection. Sociological Methods and Research, 33(2), 261-304.

bic, ictab
data(mtcars)