| sm.surface3d {sm} | R Documentation |
This function adds a regression surface, defined by a matrix of heights
at a regular grid of values of two covariates, to an rgl plot.
Missing values can be accommodated.
sm.surface3d(eval.points, surf, scaling,
col = "green", col.mesh = "black",
alpha = 0.7, alpha.mesh = 1, lit = TRUE, ...)
eval.points |
a two-column matrix defining the marginal grids of covariate values. |
surf |
a matrix of heights corresponding to the grid of covariate values. NAs are allowed. |
scaling |
a function to define the scaling for the rgl plot. This
function is returned by an initial call to rp.plot3d in the
rpanel package.
|
col |
the colour of the surface. If col is set to a single value, this
is replicated across the two components. However, a matrix of values
corresponding to the entries of surf can also be supplied.
|
col.mesh |
the colour of the surface mesh. If col.mesh is set to a single value, this
is replicated across the two components. However, a matrix of values
corresponding to the entries of surf can also be supplied.
|
alpha |
the transparency of the filled triangles defining the surface. Setting
this to 0 will remove the filled triangles from the plot.
|
alpha.mesh |
the transparency of the lines drawn across the regular grid of covariate
values. Setting this to 0 will remove the lines from the plot.
|
lit |
a logical variable which controls whether the rgl plot is lit or not.
|
... |
other optional parameters which are passed to material3d in the
rgl package.
|
the principal motivation for this function is that is can handle missing
data in regression surfaces. In particular, it can be used to plot the
results of applying sm.regression. In addition, the function can
be used to build up more complex plots by adding successive surfaces.
a vector of length 2 containing the ids of the filled surface and lines
aded to the rgl plot.
a surface is added to the rgl plot.
provide.data(trawl)
Zone93 <- (Year == 1 & Zone == 1)
Position <- cbind(Longitude - 143, Latitude)
model1 <- sm.regression(Position[Zone93,], Score1[Zone93],
h= c(0.1, 0.1), display = "rgl", xlab="Longitude - 143")
model2 <- sm.regression(Position[Zone93,], Score1[Zone93],
h= c(0.2, 0.2), display = "none")
sm.surface3d(model2$eval.points, model2$est, model1$scaling, col = "red")