[R] how to add points/lines to a surface plot

David Winsemius dwinsemius at comcast.net
Tue Feb 10 18:30:34 CET 2009

```In this case, following your instructions and a bit of noodling with
the example "solves" the problem with:

persp(teta1, teta2, matrixMuSigma) -> res
points(trans3d( teta1, sigmaMax, apply(matrixMuSigma, 1, max),
pmat=res), col="red")

--
David Winsemius

On Feb 10, 2009, at 11:50 AM, Uwe Ligges wrote:

> See ?persp, particularly the example that starts with
> # (2) Add to existing persp plot - using trans3d() :
>
> Uwe Ligges
>
>
> Domenico Vistocco wrote:
>> Dear All,
>> is there a way to superimpose points and/or lines on a surface plot?
>> Below I try to explain my problem.
>> Suppose I have the following surface plot (likelikood for the
>> normal variable when both parameters are unknown):
>> ------------------------------------------------------------------------------------------------------------------------------------------- normalLike
>>  <- function(mu, sigma, sample){
>>   (sigma ^ - length(sample)) * exp(-0.5 * (sigma ^ -2) *
>> sum((sample - mu)^2))
>> }
>> normalLikeVec <- Vectorize(normalLike,  vectorize.args =
>> c("mu","sigma"))
>> teta1 <- seq(0, 6, by=0.1)
>> teta2 <- seq(0.1, 8, by=0.1)
>> matrixMuSigma <- outer(teta1, teta2, normalLikeVec, sample=c(0.88,
>> 1.07, 1.27,1.54, 1.91, 2.27, 3.84, 4.50, 4.64, 9.41))
>> matrixMuSigma <- matrixMuSigma / max(matrixMuSigma)
>> persp(teta1, teta2, matrixMuSigma)
>> ------------------------------------------------------------------------------------------------------------------------------------------- Then
>>  I would like to superimpose on the same plot points (or a line)
>> corresponding to the following data:
>> ------------------------------------------------------------------------------------------------------------------------------------------- #x
>>  coordinates
>> teta1
>> #y coordinates
>> sigmaMax <- teta2[apply(matrixMuSigma, 1, which.max)]
>> #z coordinates
>> apply(matrixMuSigma, 1, max)
>> ------------------------------------------------------------------------------------------------------------------------------------------- Thanks
>> domenico
>> PS:
>> I am trying to explain the geometrical interpretation of profile
>> likelihood. Any better idea?
>> ______________________________________________
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