1 files changed, 0 insertions, 80 deletions
diff --git a/trunk/chemCal/R/calplot.R b/trunk/chemCal/R/calplot.R
deleted file mode 100644
index 6aed9c0..0000000
--- a/trunk/chemCal/R/calplot.R
+++ /dev/null
@@ -1,80 +0,0 @@
-calplot <- function(object, 
-  xlim = c("auto", "auto"), ylim = c("auto", "auto"), 
-  xlab = "Concentration", ylab = "Response", alpha = 0.05,
-  varfunc = NULL)
-{
-  UseMethod("calplot")
-}
-
-calplot.default <- function(object, 
-  xlim = c("auto","auto"), ylim = c("auto","auto"), 
-  xlab = "Concentration", ylab = "Response",
-  alpha=0.05, varfunc = NULL)
-{
-  stop("Calibration plots only implemented for univariate lm objects.")
-}
-
-calplot.lm <- function(object,
-  xlim = c("auto","auto"), ylim = c("auto","auto"), 
-  xlab = "Concentration", ylab = "Response", alpha=0.05,
-  varfunc = NULL)
-{
-  if (length(object$coef) > 2)
-    stop("More than one independent variable in your model - not implemented")
-
-  if (alpha <= 0 | alpha >= 1)
-    stop("Alpha should be between 0 and 1 (exclusive)")
-
-  m <- object
-  level <- 1 - alpha
-  y <- m$model[[1]]
-  x <- m$model[[2]]
-  if (xlim[1] == "auto") xlim[1] <- 0
-  if (xlim[2] == "auto") xlim[2] <- max(x)
-  xlim <- as.numeric(xlim)
-  newdata <- list(
-    x = seq(from = xlim[[1]], to = xlim[[2]], length=250))
-  names(newdata) <- names(m$model)[[2]]
-  if (is.null(varfunc)) {
-    varfunc <- if (length(m$weights)) {
-        function(variable) mean(m$weights)
-      } else function(variable) rep(1,250)
-  }
-  pred.lim <- predict(m, newdata, interval = "prediction",
-    level=level, weights.newdata = varfunc(m))
-  conf.lim <- predict(m, newdata, interval = "confidence",
-    level=level)
-  yrange.auto <- range(c(0,pred.lim))
-  if (ylim[1] == "auto") ylim[1] <- yrange.auto[1]
-  if (ylim[2] == "auto") ylim[2] <- yrange.auto[2]
-  plot(1,
-    type = "n", 
-    xlab = xlab,
-    ylab = ylab,
-    xlim = as.numeric(xlim),
-    ylim = as.numeric(ylim)
-  )
-  points(x,y, pch = 21, bg = "yellow")
-  matlines(newdata[[1]], pred.lim, lty = c(1, 4, 4), 
-    col = c("black", "red", "red"))
-  if (length(object$weights) > 0) {
-    legend(min(x), 
-      max(pred.lim, na.rm = TRUE), 
-      legend = c("Fitted Line", "Confidence Bands"),
-      lty = c(1, 3), 
-      lwd = 2, 
-      col = c("black", "green4"), 
-      horiz = FALSE, cex = 0.9, bg = "gray95")
-  } else {
-  matlines(newdata[[1]], 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")
-  }
-}