I'm not aware of explicit functions to do the job, but there are
some little tricks that make it pretty simple from the command
line interface. Suppose you fit a regression of the form
> fm <- lm(y ~ x1 + x2 + x3 + x4 + x5 + x6, data = dat)
and you want the partial residual plot of y on x5 to check for
curvature, let's say. You can do the plot in one step as
> plot(resid(update(fm, cbind(x5, y) ~ . - x5)),
xlab = "Adjusted X5", ylab = "Partial Y residuals")
The second line is not needed if you don't mind obscure axis
labels.
Stepping through all x-variables might be a bit tricky to do in a
general function if you wanted to allow for factor terms, for
example, but something sensible could be done, I suppose.
Bill Venables.
-- Bill Venables, Head, Dept of Statistics, Tel.: +61 8 8303 5418 University of Adelaide, Fax.: +61 8 8303 3696 South AUSTRALIA. 5005. Email: Bill.Venables@adelaide.edu.au----------------------------------------------------------------------- This message was distributed by s-news@wubios.wustl.edu. To unsubscribe send e-mail to s-news-request@wubios.wustl.edu with the BODY of the message: unsubscribe s-news