- Fixed the inverse prediction

- Now I have a working approach for the calculation of LOD and LOQ,
  but it seems to be different from what everybody else is doing
  (e.g. Massart chaper 13). I like it, however. Maybe it even 
  yields a paper.



git-svn-id: http://kriemhild.uft.uni-bremen.de/svn/chemCal@8 5fad18fb-23f0-0310-ab10-e59a3bee62b4

1 files changed, 11 insertions, 1 deletions

diff --git a/man/din32645.Rd b/man/din32645.Rd
index 1a3c046..d251b7c 100644
--- a/man/din32645.Rd
+++ b/man/din32645.Rd
@@ -13,9 +13,19 @@
 data(din32645)
 m <- lm(y ~ x, data=din32645)
 calplot(m)
-prediction <- inverse.predict(m,3500,alpha=0.01)
+(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)
+
+# According to Dintest, we should get 0.07, but we get 0.0759
+lod(m, alpha = 0.01)
+
+# In German, there is the "Erfassungsgrenze", with k = 2, 
+# and we should get 0.14 according to Dintest
+lod(m, k = 2, alpha = 0.01)
+
+# According to Dintest, we should get 0.21, we get 0.212
+loq(m, alpha = 0.01)
 }
 \references{
   DIN 32645 (equivalent to ISO 11843)