aic.calc: Akaike Information Criterion with correction for sample size
In levisc8/spind: Spatial Methods and Indices

aic.calc

R Documentation

Akaike Information Criterion with correction for sample size

Description

Calculates AIC and AICc

Usage

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

Arguments

`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

Value

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

Author(s)

Gudrun Carl, Sam Levin

Examples

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

levisc8/spind documentation built on April 3, 2024, 4:52 a.m.