On Nov 7, 2012, at 4:03 PM, Alexander Shenkin <ashen...@ufl.edu> wrote:
> Hello, > > I'm trying to extract the independent variables from a formula. The > closest I've been able to come, aside from rolling my own, is the following: > >> a = y ~ b * x >> attr(terms(formula(a)),"variables") > > The reason I'm doing this is that I'm building a grid of points that I > use to construct a 3-d model prediction surface in rgl. If there are > more than two independent variables, I need to set the other ones to 0 > in the dataframe for the predict() routine. In order to do that, I need > to know what those variables are. > > I suspect there's a better way to go about doing what I'm doing (perhaps > using the model.* family of functions). But, in the meantime, just > extracting the independent variables will move me forward. > > Thanks, > Allie You might want to look at ?all.vars as one possible approach. The nice thing about all.vars() is that if you have transformations on the IV's in the formula (eg. poly(x, 3)), you will get the base variable names (eg. 'x', rather than 'poly(x, 3)'). A general approach would be: all.vars(formula(MODEL)) where the response variable would typically be the first element in the returned vector. So, if you just want the IV's you could use: all.vars(formula(MODEL))[-1] An example: # from ?cars fm1 <- lm(log(dist) ~ log(speed), data = cars) > all.vars(formula(fm1)) [1] "dist" "speed" Regards, Marc Schwartz ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
