aic.calc: Akaike Information Criterion with correction for sample size
In spind: Spatial Methods and Indices

Description Usage Arguments Value Author(s) Examples

Calculates AIC and AICc

1	aic.calc(formula, family, data, mu, n.eff = NULL)

`formula`	A model formula
`family`	Family used to fit the model. `gaussian`, `binomial`, or `poisson` are supported
`data`	A data frame
`mu`	Fitted values from a model
`n.eff`	Effective number of observations. Default is NULL

A list with the following components

loglik: Log likelihood of the model
df: Degrees of freedom
AIC: AIC score for the specified model
AICc: AIC score corrected for small sample sizes

Gudrun Carl, Sam Levin

data(musdata)
coords <- musdata[ ,4:5]
mglm <- glm(musculus ~ pollution + exposure, "poisson", musdata)

aic <- aic.calc(musculus ~ pollution + exposure, "poisson", musdata,
                mglm$fitted)
aic$AIC