diff options
| author | ranke <ranke@5fad18fb-23f0-0310-ab10-e59a3bee62b4> | 2006-05-12 21:59:33 +0000 |
|---|---|---|
| committer | ranke <ranke@5fad18fb-23f0-0310-ab10-e59a3bee62b4> | 2006-05-12 21:59:33 +0000 |
| commit | 69504b635d388507bce650c44b3bfe17cad3383e (patch) | |
| tree | 120114ff6dc2d1aeb4716efef90d71257ac47501 /demo | |
| parent | 6d118690c0cae02fc5cd4b28c1a67eecde4d9f60 (diff) | |
- 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
Diffstat (limited to 'demo')
| -rw-r--r-- | demo/00Index | 1 | ||||
| -rw-r--r-- | demo/massart97ex3.R | 15 | ||||
| -rw-r--r-- | demo/massart97ex8.R | 6 |
3 files changed, 3 insertions, 19 deletions
diff --git a/demo/00Index b/demo/00Index index 8749adf..a548abc 100644 --- a/demo/00Index +++ b/demo/00Index @@ -1,2 +1 @@ -massart97ex3 Analysis of example 3 in Massart (1997) massart97ex8 Analysis of example 8 in Massart (1997) diff --git a/demo/massart97ex3.R b/demo/massart97ex3.R deleted file mode 100644 index 731aba6..0000000 --- a/demo/massart97ex3.R +++ /dev/null @@ -1,15 +0,0 @@ -library(chemCal) -data(massart97ex3) -attach(massart97ex3) -yx <- split(y,factor(x)) -ybar <- sapply(yx,mean) -s <- round(sapply(yx,sd),digits=2) -w <- round(1/(si^2),digits=3) -data.frame(x=levels(factor(x)),ybar,s,w) - -weights <- w[factor(x)] -m <- lm(y ~ x,w=weights) -inverse.predict(m,15,ws=1.67) -inverse.predict(m,90,ws=0.145) - -calplot(m) diff --git a/demo/massart97ex8.R b/demo/massart97ex8.R index 332bd1d..dca065f 100644 --- a/demo/massart97ex8.R +++ b/demo/massart97ex8.R @@ -1,4 +1,3 @@ -library(chemCal) data(massart97ex3) attach(massart97ex3) xi <- levels(factor(x)) @@ -8,5 +7,6 @@ si <- round(sapply(yx,sd),digits=2) wi <- round(1/(si^2),digits=3) weights <- wi[factor(x)] m <- lm(y ~ x,w=weights) -inverse.predict(m,15) -inverse.predict(m,90) +inverse.predict(m, 15, ws = 1.67) +inverse.predict(m, 90, ws = 0.145) +calplot(m) |