Description Usage Arguments Details Author(s) See Also Examples
View source: R/panel.2dsmoother.R
Plot a smooth approximation, using loess by default, of
one variable (z) against two others (x and y).
This panel function should be used with a levelplot.
| 1 2 3 | panel.2dsmoother(x, y, z, subscripts = TRUE,
    form = z ~ x * y, method = "loess", ...,
    args = list(), n = 100)
 | 
| x, y, z | data points. If these are missing, they will be looked for in the
environment of  | 
| form, method | the smoothing model is constructed (approximately) as
 | 
| subscripts | data indices for the current packet, as passed in by  | 
| ... | further arguments passed on to  | 
| args | a list of further arguments to the model function ( | 
| n | number of equi-spaced points along each of x and y on which to evaluate the smooth function. | 
This should work with any model function that takes a formula
argument, and has a predict method argument.
Felix Andrews felix@nfrac.org
| 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 | set.seed(1)
xyz <- data.frame(x = rnorm(100), y = rnorm(100))
xyz$z <- with(xyz, x * y + rnorm(100, sd = 1))
levelplot(z ~ x * y, xyz, panel = panel.2dsmoother)
## showing data points on the same color scale
levelplot(z ~ x * y, xyz,
          panel = panel.levelplot.points, cex = 1.2) +
  layer_(panel.2dsmoother(..., n = 200))
## simple linear regression model
levelplot(z ~ x * y, xyz,
          panel = panel.levelplot.points) +
  layer_(panel.2dsmoother(..., method = "lm"))
## GAM smoother with smoothness by cross validation
if (require("mgcv"))
  levelplot(z ~ x * y, xyz, panel = panel.2dsmoother,
            form = z ~ s(x, y), method = "gam")
 | 
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