AIC.oglmx: Calculate Akaike Information Criterion

Description Usage Arguments Details Value Author(s) See Also

View source: R/genOutput.R

Description

Calculates the Akaike Information Criterion for objects of class oglmx. Calculate using the formula -2*loglikelihood + k*npar where npar represents the number of parameters in the model and k is the cost of additional parameters, equal to 2 for the AIC, it is k=\log(n) with n the number of observations for the BIC.

Usage

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  ## S3 method for class 'oglmx'
AIC(object, ..., k = 2)

Arguments

object

object of class oglmx

...

additional arguments. Currently ignored.

k

the penalty per parameter to be used.

Details

When comparing models by maximium likelihood estimation the smaller the value of the AIC the better.

Value

A numeric value with the AIC.

Author(s)

Nathan Carroll, [email protected]

See Also

AIC.


oglmx documentation built on May 5, 2018, 5:04 p.m.