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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$y
newdata <- data.frame(x = seq(0,max(x),length=250))
pred.lim <- predict(m, newdata, interval = "prediction",level=level)
conf.lim <- predict(m, newdata, interval = "confidence",level=level)
if (xlim == "auto") xlim = c(0,max(x))
if (ylim == "auto") ylim = range(c(pred.lim,y,0))
plot(1,
type = "n",
xlab = xlab,
ylab = ylab,
xlim = xlim,
ylim = ylim
)
points(x,y, pch = 21, bg = "yellow")
matlines(newdata$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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