Description Usage Arguments Details Value See Also
View source: R/summarize_extract.R
A function calculating Akaike's Information Criterion (AIC) based on the log-likelihood
value extracted from logLik.cmp
, according to the formula
-2log-likelihood + knpar, where npar represents the number of parameters
in the fitted model, and k=2 for the usual AIC or k=log(n) (n being
the number of observations) for the so-called BIC (Bayesian Information Criterion).
1 2 |
object |
an object class 'cmp' object, obtained from a call to |
... |
other arguments passed to or from other methods (currently unused). |
k |
numeric: the penalty per parameter to be used; the default k = 2 is the classical AIC. |
When comparing models fitted by maximum likelihood to the same data, the smaller the AIC or BIC, the better the fit.
A numeric value with the corresponding AIC (or BIC, or ..., depends on k).
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