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(fit, scale, 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, fit a fit inheriting from class "trls"
scale unused for this method
k the multiple of the number of degrees of freedom to be used.
... arguments passed to or from other methods.

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")

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