-----Original Message-----
From: r-help-bounces at stat.math.ethz.ch
[mailto:r-help-bounces at stat.math.ethz.ch] On Behalf Of Prof
Brian Ripley
Sent: Thursday, March 31, 2005 10:58 AM
To: Johannes Ullrich
Cc: r-help at stat.math.ethz.ch
Subject: Re: [R] Surface plot for polynomial regression
Please note there is no `scatter3d' function in R.
There is one in John Fox's package Rcmdr: please give credit
where it is due.
However, I think you have overlooked functions like persp,
image, contour, cloud wireframe and levelplot (lattice), all
of which can plot any function of two variables and whose
examples (and some of the demos) show you how. You might
also want to look at rgl.surface (package rgl).
On Thu, 31 Mar 2005, Johannes Ullrich wrote:
Dear R-experts,
my goal is to visualize the following polynomial regression
as a 3D-surface:
It is a 2D surface, by any reasonable definition of `dimension'.
Z = b0 + b1*X + b2*Y + b3*XY + b4*X^2 + b5*Y^2
I believe that a solution to this problem may be of interest to a
wider range of scientists because the problem is a derivative of a
more general problem, i.e.: how to describe the
one dependent variable and the DIFFERENCE between two other
There are numerous problems associated with difference
reliability). One suggested alternative consists of using the
components of the difference score separately in polynomial
regression. So this is how I ended up with the above
regression, which is essentially a reformulation of b1*(X-Y)^2.
After consulting the help pages and archives my best guess was that
the function scatter3d could be rewritten in part to
produce the desired output.
In fact, the quadratic fit output of the scatter3d function comes
closest to what I have in mind. However, I think the XY term is
missing from the quadratic fit equation. When I use wireframe to
visualize the raw data, there is a peak of the dependent
both X AND Y are high. Yet this peak does not appear in the
quadratic fit of scatter3d.
Any pointers would be welcome. I should add that I am not a
and mainly work with high-level functions.
Thank you very much for R and for your help
Johannes
Dipl.-Psych. Johannes Ullrich
Philipps-Universit?t Marburg
Germany