Started a new approach, namely just adding a inverse.predict

method for univariate lm models. This will be based on Massart,
p. 200.



git-svn-id: http://kriemhild.uft.uni-bremen.de/svn/chemCal@3 5fad18fb-23f0-0310-ab10-e59a3bee62b4

1 files changed, 40 insertions, 0 deletions

diff --git a/R/inverse.predict.lm.R b/R/inverse.predict.lm.R
new file mode 100644
index 0000000..f438d99
--- /dev/null
+++ b/R/inverse.predict.lm.R
@@ -0,0 +1,40 @@
+# This is an implementation of Equation (8.28) in the Handbook of Chemometrics
+# and Qualimetrics, Part A, Massart et al, page 200, validated with Example 8
+# on the same page
+
+inverse.predict <- function(object, newdata, alpha=0.05)
+{
+  UseMethod("inverse.predict")
+}
+
+inverse.predict.default <- function(object, newdata, alpha=0.05)
+{
+  stop("Inverse prediction only implemented for univariate lm objects.")
+}
+
+inverse.predict.lm <- function(object, newdata, alpha=0.05)
+{
+  if (is.list(newdata)) {
+    if (!is.null(newdata$y))
+      newdata <- newdata$y
+    else
+      stop("Newdata list should contain element newdata$y")
+  }
+
+  if (is.matrix(newdata)) {
+    Y <- newdata
+    Ybar <- apply(Y,1,mean)
+    nrepl <- ncol(Y)
+  }
+  else {
+    Y <- as.vector(newdata)
+    Ybar <- Y
+    nrepl <- 1 
+  }
+
+  if (length(object$coef) > 2)
+    stop("Inverse prediction not yet implemented for more than one independent variable")
+
+  if (alpha <= 0 | alpha >= 1)
+    stop("Alpha should be between 0 and 1 (exclusive)")
+}