Hi All,
Does anyone know of a function to plot a regression surface for two
predictors? RSiteSearch()s and findFn()s have not turned up what I
was looking for. I was thinking something along the lines of:
http://mallit.fr.umn.edu/fr5218/reg_refresh/images/fig9.gif
I like the rgl package because showing it from different angles is
nice for demonstrations. I started to write my own, but it has some
issues (non functioning code start below), and I figured before I
tried to work out the kinks, I would ask for the list's feedback.
Any comments or suggestions (about functions or preferred idioms for
what I tried below, or...) are greatly appreciated.
Josh
RegSurfaceDemo <- function(formula, data, xlim, ylim, zlim,
resolution = 100) {
require(rgl)
## This cannot be the proper way to extract variable names from formula
vars <- rownames(attr(terms(formula), "factors"))
## if no limits set, make them nearest integer to
## .75 the lowest value and 1.25 the highest
ranger <- function(x) {
as.integer(range(x) * c(.75, 1.25))
}
if(is.null(xlim)) {xlim <- ranger(data[, vars[2]])}
if(is.null(ylim)) {ylim <- ranger(data[, vars[3]])}
if(is.null(zlim)) {zlim <- ranger(data[, vars[1]])}
## This does not actually work because the data frame
## does not get named properly (actually it throws an error)
##f <- function (x, y) {
## predict(my.model, newdata = data.frame(vars[2] = x, vars[3] = y))
##}
## Fit model
my.model <- lm(formula = formula, data = data)
## Create X, Y, and Z grids
X <- seq(from = xlim[1], to = xlim[2], length.out = resolution)
Y <- seq(from = ylim[1], to = ylim[2], length.out = resolution)
Z <- outer(X, Y, f)
## Create 3d scatter plot and add the regression surface
open3d()
with(data = data,
plot3d(x = vars[2], y = vars[3], z = vars[1],
xlim = xlim, ylim = ylim, zlim = zlim))
par3d(ignoreExtent = TRUE)
surface3d(X, Y, Z, col = "blue", alpha = .6)
par3d(ignoreExtent = FALSE)
return(summary(my.model))
}
--
Joshua Wiley
Ph.D. Student, Health Psychology
University of California, Los Angeles
http://www.joshuawiley.com/
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