- The vignette is in a publisheable state

- In addition to the Massart examples, the sample data from dintest (DIN 32645)
  has been tested
- inverse.predict and calplot now also work on glm objects



git-svn-id: http://kriemhild.uft.uni-bremen.de/svn/chemCal@7 5fad18fb-23f0-0310-ab10-e59a3bee62b4

1 files changed, 14 insertions, 2 deletions

diff --git a/man/din32645.Rd b/man/din32645.Rd
index 0a2a790..1a3c046 100644
--- a/man/din32645.Rd
+++ b/man/din32645.Rd
@@ -9,7 +9,19 @@
 \format{
   A dataframe containing 10 rows of x and y values.
 }
-\source{
-  \url{http://www.uft.uni-bremen.de/chemie}
+\examples{
+data(din32645)
+m <- lm(y ~ x, data=din32645)
+calplot(m)
+prediction <- inverse.predict(m,3500,alpha=0.01)
+# This should give 0.074 according to DIN (cited from the Dintest test data)
+round(prediction$Confidence,3)
+}
+\references{
+  DIN 32645 (equivalent to ISO 11843)
+
+  Dintest. Plugin for MS Excel for evaluations of calibration data. Written
+  by Georg Schmitt, University of Heidelberg. 
+  \url{http://www.rzuser.uni-heidelberg.de/~df6/download/dintest.htm}
 }
 \keyword{datasets}