- 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, 25 insertions, 0 deletions

diff --git a/R/lod.R b/R/lod.R
new file mode 100644
index 0000000..9f90d48
--- /dev/null
+++ b/R/lod.R
@@ -0,0 +1,25 @@
+lod <- function(object, ..., alpha = 0.05, k = 1, n = 1, w = "auto")
+{
+  UseMethod("lod")
+}
+
+loq <- function(object, ..., alpha = 0.05, k = 3, n = 1, w = "auto")
+{
+  lod(object = object, alpha = alpha, k = k, n = n, w = w)
+}
+
+lod.default <- function(object, ..., alpha = 0.05, k = 1, n = 1, w = "auto")
+{
+  stop("lod is only implemented for univariate lm objects.")
+}
+
+lod.lm <- function(object, ..., alpha = 0.05, k = 1, n = 1, w = "auto")
+{
+  f <- function(x) {
+    y <- predict(object, data.frame(x = x))
+    p <- inverse.predict(object, rep(y, n), ws = w, alpha = alpha)
+    (p[["Prediction"]] - k * p[["Confidence"]])^2
+  }
+  tmp <- optimize(f,interval=c(0,max(object$model$x)))
+  return(tmp$minimum)
+}