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\name{AIC.mmkin}
\alias{AIC.mmkin}
\title{
Calculated the AIC for a column of an mmkin object
}
\description{
Provides a convenient way to compare different kineti models fitted to the
same dataset.
}
\usage{
\method{AIC}{mmkin}(object, ..., k = 2)
}
\arguments{
\item{object}{
An object of class \code{\link{mmkin}}, containing only one column.
}
\item{\dots}{
For compatibility with the generic method
}
\item{k}{
As in the generic method
}
}
\value{
As in the generic method (a numeric value for single fits, or a dataframe if
there are several fits in the column).
}
\examples{
f <- mmkin(c("SFO", "FOMC", "DFOP"),
list("FOCUS A" = FOCUS_2006_A,
"FOCUS C" = FOCUS_2006_C), cores = 1, quiet = TRUE)
AIC(f[1, "FOCUS A"]) # We get a single number for a single fit
# For FOCUS A, the models fit almost equally well, so the higher the number
# of parameters, the higher (worse) the AIC
AIC(f[, "FOCUS A"])
AIC(f[, "FOCUS A"], k = 0) # If we do not penalize additional parameters, we get nearly the same
# For FOCUS C, the more complex models fit better
AIC(f[, "FOCUS C"])
}
\author{
Johannes Ranke
}
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