Given a log-likelihood, the number of observations and the number of estimated parameters, the average value of a chosen information criterion is computed. This facilitates comparison of models that are estimated with a different number of observations, e.g. due to different lags.
infocrit(x, method=c("sc","aic","aicc","hq"))info.criterion(logl, n=NULL, k=NULL, method=c("sc","aic","aicc","hq"))
a list that contains, at least, three items: logl (a numeric, the log-likelihood), k (a numeric, usually the number of estimated parameters) and n (a numeric, the number of observations)
character, either "sc" (default), "aic", "aicc" or "hq"
numeric, the value of the log-likelihood
integer, number of observations
integer, number of parameters
infocrit: a numeric (i.e. the value of the chosen information criterion)
info.criterion: a list with elements
type of information criterion
number of observations
number of parameters
the value on the information criterion
Contrary to AIC and BIC, info.criterion computes the average criterion value (i.e. division by the number of observations). This facilitates comparison of models that are estimated with a different number of observations, e.g. due to different lags.
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