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\name{calplot}
\alias{calplot}
\alias{calplot.default}
\alias{calplot.lm}
\title{Plot calibration graphs from univariate linear models}
\description{
Produce graphics of calibration data, the fitted model as well
as confidence, and, for unweighted regression, prediction bands.
}
\usage{
calplot(object, xlim = c("auto", "auto"), ylim = c("auto", "auto"),
xlab = "Concentration", ylab = "Response", alpha=0.05, varfunc = NULL)
}
\arguments{
\item{object}{
A univariate model object of class \code{\link{lm}} or
\code{\link[MASS:rlm]{rlm}}
with model formula \code{y ~ x} or \code{y ~ x - 1}.
}
\item{xlim}{
The limits of the plot on the x axis.
}
\item{ylim}{
The limits of the plot on the y axis.
}
\item{xlab}{
The label of the x axis.
}
\item{ylab}{
The label of the y axis.
}
\item{alpha}{
The error tolerance level for the confidence and prediction bands.
}
\item{varfunc}{
The variance function for generating the weights in the model.
Currently, this argument is ignored (see note below).
}
}
\value{
A plot of the calibration data, of your fitted model as well as lines showing
the confidence limits. Prediction limits are only shown for models from
unweighted regression.
}
\note{
Prediction bands for models from weighted linear regression require weights
for the data, for which responses should be predicted. Prediction intervals
for weighted models are not currently supported by the internally used
function \code{\link{predict.lm}}, therefore, \code{calplot} refuses to work
for such models.
}
\examples{
data(massart97ex3)
m <- lm(y ~ x, data = massart97ex3)
calplot(m)
}
\author{
Johannes Ranke
\email{jranke@uni-bremen.de}
\url{http://www.uft.uni-bremen.de/chemie/ranke}
}
\keyword{regression}
|
