| surf.ls {spatial} | R Documentation |
Fits a Trend Surface by Least-squares
Description
Fits a trend surface by least-squares.
Usage
surf.ls(np, x, y, z)
residuals(object, ...)
fitted(object, ...)
deviance(object, ...)
df.residual(object, ...)
extractAIC(object, k=2, ...)
Arguments
np |
degree of polynomial surface
|
x |
x coordinates or a data frame with columns x, y, z
|
y |
y coordinates
|
z |
z coordinates. Will supersede x$z
|
object |
a fit inheriting from class "trls"
|
Value
list with components
beta |
the coefficients
|
x |
|
y |
|
z |
and others for internal use only.
|
See Also
trmat, surf.gls
Examples
library(MASS)
data(topo)
topo.kr <- surf.ls(2, topo)
trsurf <- trmat(topo.kr, 0, 6.5, 0, 6.5, 50)
eqscplot(trsurf, type="n")
contour(trsurf, add=TRUE)
points(topo)
eqscplot(trsurf, type="n")
contour(trsurf, add=TRUE)
plot(topo.kr, add=TRUE)
title(xlab="Circle radius proportional to Cook's influence statistic")