plot with a regression line(s)

-----Original Message-----
From: r-help-bounces at r-project.org 
[mailto:r-help-bounces at r-project.org] On Behalf Of Sam Steingold

plot.glm <- function (x, y, file = NULL, xlab = 
deparse(substitute(x)),
                      ylab = deparse(substitute(y)), main = NULL) {
  m <- glm(y ~ x)
  if (!is.null(file))
    pdf(file = file)
  plot(x, y, xlab = xlab, ylab = ylab, main = main)
  lines(x, y = m$fitted.values, col = "green")
  if (!is.null(file))
    dev.off()
  print(m)
}

is there a better/easier/more general way?

There is no guarantee that x is sorted in ascending order for a glm (or any other model), so lines(x, fitted()) can give very spiny results. Even if sorted, non-linear fits with large gaps in x will not give smooth lines.

Better to use something along the lines of the budworm example in the glm help page, which uses predict() on a new sequence.
If you want something a bit more general, you can use either range(x) to get the new sequence limits or  par("usr")[1:2]  to gets the current plot x limits.


S Ellison
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