akaikeic: Akaike Information Criterion

Description Usage Arguments Details Value See Also Examples

View source: R/EvaluationCriteria.R

Description

akaikeic calculates the Akaike Information Criterion (AIC) of a model.
akaikeicc calculates the corrected Akaike Information Criterion (AICc) for small samples.

Usage

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akaikeic(NLL, k)

akaikeicc(NLL, k, n)

Arguments

NLL

Negative Log-Likelihood of the model.

k

Number of parameters of the model.

n

Sample size.

Details

AIC = 2 * k + 2 * NLL

AICc = 2 * k - 2 * lnL + 2 * k * (k + 1) / (n - k - 1)

Value

A number with the AIC value for a model with k parameters and negative log-likelihood NLL, or the AICc value for a model with k parameters, negative log-likelihood NLL and sample size n.

See Also

weight_of_evidence

Examples

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akaikeic(1485.926, 3)
akaikeicc(736.47, 6, 15)
akaikeicc(736.47, 6, 100)

island documentation built on May 10, 2018, 9:04 a.m.