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authorranke <ranke@5fad18fb-23f0-0310-ab10-e59a3bee62b4>2006-05-12 21:59:33 +0000
committerranke <ranke@5fad18fb-23f0-0310-ab10-e59a3bee62b4>2006-05-12 21:59:33 +0000
commit69504b635d388507bce650c44b3bfe17cad3383e (patch)
tree120114ff6dc2d1aeb4716efef90d71257ac47501 /R/calplot.R
parent6d118690c0cae02fc5cd4b28c1a67eecde4d9f60 (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 'R/calplot.R')
-rw-r--r--R/calplot.R2
1 files changed, 1 insertions, 1 deletions
diff --git a/R/calplot.R b/R/calplot.R
index cea1149..feb9727 100644
--- a/R/calplot.R
+++ b/R/calplot.R
@@ -27,7 +27,7 @@ calplot.lm <- function(object, xlim = "auto", ylim = "auto",
pred.lim <- predict(m, newdata, interval = "prediction",level=level)
conf.lim <- predict(m, newdata, interval = "confidence",level=level)
if (xlim == "auto") xlim = c(0,max(x))
- if (ylim == "auto") ylim = range(c(pred.lim,y))
+ if (ylim == "auto") ylim = range(c(pred.lim,y,0))
plot(1,
type = "n",
xlab = xlab,

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