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-rw-r--r--R/calplot.R52
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diff --git a/R/calplot.R b/R/calplot.R
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+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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