From 966da79af48c371c05dd8011702ef2bd3b1d1e03 Mon Sep 17 00:00:00 2001
From: Johannes Ranke
calplot(object, xlim = c("auto", "auto"), ylim = c("auto", "auto"), +calplot(object, xlim = c("auto", "auto"), ylim = c("auto", "auto"), xlab = "Concentration", ylab = "Response", alpha=0.05, varfunc = NULL)Arguments
-
lm
or
+ object | +A univariate model object of class y ~ x or y ~ x - 1 . |
+
---|---|
xlim | +The limits of the plot on the x axis. |
+
ylim | +The limits of the plot on the y axis. |
+
xlab | +The label of the x axis. |
+
ylab | +The label of the y axis. |
+
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 lod (see note below). |
+
varfunc | +The variance function for generating the weights in the model. + Currently, this argument is ignored (see note below). |
+
predict.lm
, therefore,
- calplot
does not draw prediction bands for such models.
- It is possible to compare the calplot
prediction bands with the
- lod
values if the lod()
alpha and beta parameters are
+ calplot
does not draw prediction bands for such models.
It is possible to compare the calplot
prediction bands with the
+ lod
values if the lod()
alpha and beta parameters are
half the value of the calplot()
alpha parameter.
+calplot(m) @@ -167,7 +178,7 @@ -- cgit v1.2.1data(massart97ex3) m <- lm(y ~ x, data = massart97ex3) -calplot(m)