On Apr 4, 2012, at 11:30 AM, R. Michael Weylandt <michael.weyla...@gmail.com
> wrote:
I'm not sure what your definition of easier would be, but there are
some style things you might want to be aware of:
I) the name is likely to hit up against the S3 generic plot() when
applied to a glm object. This might lead to strange bugs at some
point.
II) you can test !is.null once and use on.exit() to delay the clean-
up call to dev.off()
III) I'm not sure about glm objects but abline() applied to an lm
object automatically plots a best fit line saving you a line or so
of code.
If you offer a regression object to abline's 'reg' parameter and that
object has a coef() method you might get a result. But if the link
function of the regression is not matched to the plot's scale (as
might happen with a logistic or poisson fit) then results may not be
as expected. Most people will probably want to use `predict(reg-
object, newdata= ...., type = "response")` with .
IV) You probably don't want to print() m at the end: the REPL will
print it automatically in interactive top level calls and it will be
rather noisy if you start wrapping this in other calls.
Hope this helps,
Michael
On Apr 4, 2012, at 11:13 AM, Sam Steingold <s...@gnu.org> wrote:
I am sure a common need is to plot a scatterplot with some fitted
line(s) and maybe save to a file.
I have this:
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?
--
David Winsemius, MD
West Hartford, CT
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