From 73e650114af77582238abf5273e63005e0b2287e Mon Sep 17 00:00:00 2001 From: Johannes Ranke Date: Mon, 6 Mar 2017 17:00:48 +0100 Subject: Static documentation now built by pkgdown::build_site() --- docs/reference/calplot.lm.html | 177 +++++++++++++++++++++++++++++++++++++++++ 1 file changed, 177 insertions(+) create mode 100644 docs/reference/calplot.lm.html (limited to 'docs/reference/calplot.lm.html') diff --git a/docs/reference/calplot.lm.html b/docs/reference/calplot.lm.html new file mode 100644 index 0000000..f66e636 --- /dev/null +++ b/docs/reference/calplot.lm.html @@ -0,0 +1,177 @@ + + + + + + + + +Plot calibration graphs from univariate linear models — calplot • chemCal + + + + + + + + + + + + + + + + + + + + + + + + +
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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.

+ + + 
calplot(object, xlim = c("auto", "auto"), ylim = c("auto", "auto"),
+    xlab = "Concentration", ylab = "Response", alpha=0.05, varfunc = NULL)
+ +

Arguments

+
+
object
+
+ A univariate model object of class lm or + rlm + with model formula 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). +
+
+ +

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 + using weights e.g. from a variance function are currently not supported by + the internally used function 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 + half the value of the calplot() alpha parameter.

+ + +

Examples

+ 
data(massart97ex3)
+m <- lm(y ~ x, data = massart97ex3)
+calplot(m)
+
+ +
+ + +
+ + + -- cgit v1.2.1