On 13-08-15 1:15 PM, David Winsemius wrote:
On Aug 15, 2013, at 2:23 AM, Lucas Holland wrote:
Hello all,
I’ve fitted a bivariate smoothing model (with GAM) to some data, using two
explanatory variables, x and y. Now I’d like to add the surface corresponding
to my fit to a 3D scatterplot generated using plot3d().
My approach so far is to create a grid of x and y values and the corresponding
predicted values and to try to use surface3d with that grid.
grid <- expand.grid(x = seq(-1,1,length=20),
y = seq(-1,1, length=20))
grid$z <- predict(fit.nonparametric, newdata=grid)
surface3d(grid$x, grid$y, matrix(grid$z, nrow=length(grid$x),
ncol=length(grid$y)))
?surface3d
# Should be:
surface3d( unique(grid$x), unique(grid$y),
z= matrix(grid$z, nrow=length(grid$x),
ncol=length(grid$y)))
Or you could make x and y into matrices as well. In this case you'll
get the same result, but if x or y weren't strictly increasing
sequences, there'd be a difference.
Duncan Murdoch
This however plots a number of surfaces that do not look like the fitted
surface obtained by vis.gam(fit.nonparametric which actually looks a lot like
the „truth“ (I’m using simulated data so I know the true regression surface).
I think I’m using surface3d wrong but I can’t seem to spot my mistake.
Always look at the Arguments section of help pages carefully.
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