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| -rw-r--r-- | R/calplot.R | 44 |
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diff --git a/R/calplot.R b/R/calplot.R index fd49a54..3c227d4 100644 --- a/R/calplot.R +++ b/R/calplot.R @@ -1,3 +1,45 @@ +#' Plot calibration graphs from univariate linear models +#' +#' Produce graphics of calibration data, the fitted model as well as +#' confidence, and, for unweighted regression, prediction bands. +#' +#' @aliases calplot calplot.default calplot.lm +#' @param 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}. +#' @param xlim The limits of the plot on the x axis. +#' @param ylim The limits of the plot on the y axis. +#' @param xlab The label of the x axis. +#' @param ylab The label of the y axis. +#' @param legend_x An optional numeric value for adjusting the x coordinate of +#' the legend. +#' @param 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). +#' @param varfunc The variance function for generating the weights in the +#' model. Currently, this argument is ignored (see note below). +#' @return 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 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. +#' @author Johannes Ranke +#' @importFrom graphics legend matlines plot points +#' @examples +#' +#' data(massart97ex3) +#' m <- lm(y ~ x, data = massart97ex3) +#' calplot(m) +#' +#' @export calplot calplot <- function(object, xlim = c("auto", "auto"), ylim = c("auto", "auto"), xlab = "Concentration", ylab = "Response", @@ -7,6 +49,7 @@ calplot <- function(object, UseMethod("calplot") } +#' @export calplot.default <- function(object, xlim = c("auto","auto"), ylim = c("auto","auto"), xlab = "Concentration", ylab = "Response", @@ -16,6 +59,7 @@ calplot.default <- function(object, stop("Calibration plots only implemented for univariate lm objects.") } +#' @export calplot.lm <- function(object, xlim = c("auto","auto"), ylim = c("auto","auto"), xlab = "Concentration", ylab = "Response", |