... or, more simply lm(z ~ polym(x,y, degree=2) )
?polym Cheers, Bert On Wed, Dec 4, 2013 at 10:30 AM, David Winsemius <dwinsem...@comcast.net> wrote: > > On Dec 4, 2013, at 8:56 AM, Duncan Murdoch wrote: > >> On 04/12/2013 11:36 AM, Jun Shen wrote: >>> Hi, >>> >>> I have a dataset with two independent variables (x, y) and a response >>> variable (z). I was hoping to generate a response surface by plotting x, y, >>> z on a three dimensional plot. I can plot the data with rgl.points(x, y, >>> z). I understand I may not have enough data to generate a surface. Is there >>> a way to smooth out the data points to generate a surface? Thanks a lot. >> >> There are many ways to do that. You need to fit a model that predicts z >> from (x, y), and then plot the predictions from that model. >> An example below follows yours. >>> >>> Jun >>> >>> =========================== >>> >>> An example: >>> >>> x<-runif(20) >>> y<-runif(20) >>> z<-runif(20) >>> >>> library(rgl) >>> rgl.points(x,y,z) >> >> Don't use rgl.points, use points3d() or plot3d(). Here's the full script: >> >> >> x<-runif(20) >> y<-runif(20) >> z<-runif(20) >> >> library(rgl) >> plot3d(x,y,z) >> >> fit <- lm(z ~ x + y + x*y + x^2 + y^2) >> > > Newcomers to R may think they would be getting a quadratic in x and y. But > R's formula interpretation will collapse x^2 to just x and then it becomes > superfluous and is discarded. The same result is obtained with z ~ (x + > y)^2). I would have thought that this would have been the code: > > fit <- lm(z ~ poly(x,2) +poly(y,2) + x:y ) > > >> xnew <- seq(min(x), max(x), len=20) >> ynew <- seq(min(y), max(y), len=20) >> df <- expand.grid(x = xnew, >> y = ynew) >> >> df$z <- predict(fit, newdata=df) >> >> surface3d(xnew, ynew, df$z, col="red") > > With the modified fitting formula one sees a nice saddle (for that particular > random draw) using rgl.snapshot(). > > > The result with the earlier formula is a more restrained: > > > > > Continued thanks to you Duncan for making this great tool available. > > -- > David. > > >> Duncan Murdoch >>> > > David Winsemius > Alameda, CA, USA > > ______________________________________________ > 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. -- Bert Gunter Genentech Nonclinical Biostatistics (650) 467-7374 ______________________________________________ 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.
