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% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/calplot.R
\name{calplot}
\alias{calplot}
\alias{calplot.default}
\alias{calplot.lm}
\title{Plot calibration graphs from univariate linear models}
\usage{
calplot(
object,
xlim = c("auto", "auto"),
ylim = c("auto", "auto"),
xlab = "Concentration",
ylab = "Response",
legend_x = "auto",
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{legend_x}{An optional numeric value for adjusting the x coordinate of
the legend.}
\item{alpha}{The error tolerance level for the confidence and prediction
bands. Note that this includes both tails of the Gaussian distribution,
unlike the alpha and beta parameters used in \code{\link{lod}} (see note
below).}
\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.
}
\description{
Produce graphics of calibration data, the fitted model as well as
confidence, and, for unweighted regression, prediction bands.
}
\note{
Prediction bands for models from weighted linear regression require
weights for the data, for which responses should be predicted. Prediction
intervals using weights e.g. from a variance function are currently not
supported by the internally used function \code{\link{predict.lm}},
therefore, \code{calplot} does not draw prediction bands for such models.
It is possible to compare the \code{\link{calplot}} prediction bands with
the \code{\link{lod}} values if the \code{lod()} alpha and beta parameters
are half the value of the \code{calplot()} alpha parameter.
}
\examples{
data(massart97ex3)
m <- lm(y ~ x, data = massart97ex3)
calplot(m)
}
\author{
Johannes Ranke
}
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