diff options
Diffstat (limited to 'man/calplot.lm.Rd')
| -rw-r--r-- | man/calplot.lm.Rd | 26 |
1 files changed, 15 insertions, 11 deletions
diff --git a/man/calplot.lm.Rd b/man/calplot.lm.Rd index 734933d..de63022 100644 --- a/man/calplot.lm.Rd +++ b/man/calplot.lm.Rd @@ -8,8 +8,9 @@ as prediction and confidence bands. } \usage{ - calplot(object, xlim = "auto", ylim = "auto", - xlab = "Concentration", ylab = "Response", alpha=0.05) + calplot(object, xlim = c("auto","auto"), ylim = c("auto","auto"), + xlab = "Concentration", ylab = "Response", alpha=0.05, + varfunc = NULL) } \arguments{ \item{object}{ @@ -32,22 +33,25 @@ \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 as well as the prediction limits. } +\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{ -# Example of a Calibration plot for a weighted regression -source("/home/ranke/tmp/r-base-2.3.0/src/library/stats/R/lm.R") data(massart97ex3) -attach(massart97ex3) -yx <- split(y,factor(x)) -s <- round(sapply(yx,sd),digits=2) -w <- round(1/(s^2),digits=3) -weights <- w[factor(x)] -m <- lm(y ~ x,w=10 * weights) -calplot(m) +m <- lm(y ~ x, data=massart97ex3) calplot(m) } \author{ |