From 513dfbdcdda94a901b5901b486ff5500c7d158b1 Mon Sep 17 00:00:00 2001
From: ranke <ranke@5fad18fb-23f0-0310-ab10-e59a3bee62b4>
Date: Wed, 10 May 2006 15:44:14 +0000
Subject: The inverse prediction works in a variety of cases and is tested with
 Examples 7 and 8 from Massart!

I need to compare with the DIN and draper examples, and finish
the package vignette.



git-svn-id: http://kriemhild.uft.uni-bremen.de/svn/chemCal@6 5fad18fb-23f0-0310-ab10-e59a3bee62b4
---
 R/calplot.R | 52 ++++++++++++++++++++++++++++++++++++++++++++++++++++
 1 file changed, 52 insertions(+)
 create mode 100644 R/calplot.R

(limited to 'R/calplot.R')

diff --git a/R/calplot.R b/R/calplot.R
new file mode 100644
index 0000000..cea1149
--- /dev/null
+++ b/R/calplot.R
@@ -0,0 +1,52 @@
+calplot <- function(object, xlim = "auto", ylim = "auto", 
+  xlab = "Concentration", ylab = "Response", alpha=0.05)
+{
+  UseMethod("calplot")
+}
+
+calplot.default <- function(object, xlim = "auto", ylim = "auto", 
+  xlab = "Concentration", ylab = "Response", alpha=0.05)
+{
+  stop("Calibration plots only implemented for univariate lm objects.")
+}
+
+calplot.lm <- function(object, xlim = "auto", ylim = "auto", 
+  xlab = "Concentration", ylab = "Response", alpha=0.05)
+{
+  if (length(object$coef) > 2)
+    stop("More than one independent variable in your model - not implemented")
+
+  if (alpha <= 0 | alpha >= 1)
+    stop("Alpha should be between 0 and 1 (exclusive)")
+
+  m <- object
+  level <- 1 - alpha
+  x <- m$model$x
+  y <- m$model$y
+  newdata <- data.frame(x = seq(0,max(x),length=250))
+  pred.lim <- predict(m, newdata, interval = "prediction",level=level)
+  conf.lim <- predict(m, newdata, interval = "confidence",level=level)
+  if (xlim == "auto") xlim = c(0,max(x))
+  if (ylim == "auto") ylim = range(c(pred.lim,y))
+  plot(1,
+    type = "n", 
+    xlab = xlab,
+    ylab = ylab,
+    xlim = xlim,
+    ylim = ylim
+  )
+  points(x,y, pch = 21, bg = "yellow")
+  matlines(newdata$x, pred.lim, lty = c(1, 4, 4), 
+    col = c("black", "red", "red"))
+  matlines(newdata$x, conf.lim, lty = c(1, 3, 3), 
+    col = c("black", "green4", "green4"))
+
+  legend(min(x), 
+    max(pred.lim, na.rm = TRUE), 
+    legend = c("Fitted Line", "Confidence Bands", 
+        "Prediction Bands"), 
+    lty = c(1, 3, 4), 
+    lwd = 2, 
+    col = c("black", "green4", "red"), 
+    horiz = FALSE, cex = 0.9, bg = "gray95")
+}
-- 
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