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)))
> 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.
--
David Winsemius
Alameda, CA, USA
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