I use the lattice package for almost everything I plot in R and it has a corresponing plot to persp called wireframe. Let data be the way Sven defined it.

wireframe(z ~ x * y, data=data)

Or how about this (modification of fig 6.3 in Deepanyan Sarkar's book):

p <- wireframe(z ~ x * y, data=data)
npanel <- c(4, 2)
rotx <- c(-50, -80)
rotz <- seq(30, 300, length = npanel[1]+1)
update(p[rep(1, prod(npanel))], layout = npanel,
    panel = function(..., screen) {
        panel.wireframe(..., screen = list(z = rotz[current.column()],
                                           x = rotx[current.row()]))
    })

I use the lattice package for almost everything I plot in R and it has a corresponing plot to persp called wireframe. Let data be the way Sven defined it.

wireframe(z ~ x * y, data=data)

Or how about this (modification of fig 6.3 in Deepanyan Sarkar's book):

p <- wireframe(z ~ x * y, data=data)
npanel <- c(4, 2)
rotx <- c(-50, -80)
rotz <- seq(30, 300, length = npanel[1]+1)
update(p[rep(1, prod(npanel))], layout = npanel,
    panel = function(..., screen) {
        panel.wireframe(..., screen = list(z = rotz[current.column()],
                                           x = rotx[current.row()]))
    })

Update: Plotting surfaces with OpenGL

Since this post continues to draw attention I want to add the OpenGL way to make 3-d plots too (as suggested by @tucson below). First we need to reformat the dataset from xyz-tripplets to axis vectors x and y and a matrix z.

x <- 1:5/10
y <- 1:5
z <- x %o% y
z <- z + .2*z*runif(25) - .1*z

library(rgl)
persp3d(x, y, z, col="skyblue")

This image can be freely rotated and scaled using the mouse, or modified with additional commands, and when you are happy with it you save it using rgl.snapshot.

rgl.snapshot("myplot.png")

I use the lattice package for almost everything I plot in R and it has a corresponing plot to persp called wireframe. Let data be the way Sven defined it.

wireframe(z ~ x * y, data=data)

Or how about this (modification of fig 6.3 in Deepanyan Sarkar's book):

p <- wireframe(z ~ x * y, data=data)
npanel <- c(4, 2)
rotx <- roty <- c(-50, -80)
rotz <- seq(30, 300, length = npanel[1]+1)
update(p[rep(1, prod(npanel))], layout = npanel,
    panel = function(..., screen) {
        crow <- current.row()
        ccol <- current.column()
        print(crow)
        panel.wireframe(..., screen = list(z = rotz[ccol], x = rotx[crow]))
    })

I use the lattice package for almost everything I plot in R and it has a corresponing plot to persp called wireframe. Let data be the way Sven defined it.

wireframe(z ~ x * y, data=data)

Or how about this (modification of fig 6.3 in Deepanyan Sarkar's book):

p <- wireframe(z ~ x * y, data=data)
npanel <- c(4, 2)
rotx <- c(-50, -80)
rotz <- seq(30, 300, length = npanel[1]+1)
update(p[rep(1, prod(npanel))], layout = npanel,
    panel = function(..., screen) {
        panel.wireframe(..., screen = list(z = rotz[current.column()],
                                           x = rotx[current.row()]))
    })