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\name{calm}
\alias{calm}
\alias{print.calm}
\alias{predict.calm}
\alias{summary.calm}
\title{Generate a calibration model}
\description{
This function fits a calibration model to the data
frame.
}
\usage{
calm(data)
}
\arguments{
\item{data}{
A data frame with numeric x data in the first column and
numeric y data in the second column.
}
}
\value{
An object of class \code{calm}, which is derived from
a linear model \code{lm}, the only difference being that
it contains the additional attributes \code{xname},
\code{yname} and \code{intercept}, the latter being a
boolean reporting wether the model uses an intercept or not.
}
\note{
The decision if the returned model contains an intercept is taken based on
the significance of the fitted intercept on a significance level of 0.95.
The methods \code{\link{print.calm}}, \code{\link{predict.calm}}
\code{\link{summary.calm}} are just newly assigned names for the
corresponding methods from the class \code{\link{lm}}.
}
\examples{
data(din32645)
calm(din32645)
}
\author{
Johannes Ranke
\email{jranke@uni-bremen.de}
\url{http://www.uft.uni-bremen.de/chemie/ranke}
}
\keyword{regression}
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