surf.gls {spatial}R Documentation

Fits a Trend Surface by Generalized Least-squares

Description

Fits a trend surface by generalized least-squares.

Usage

surf.gls(np, covmod, x, y, z, nx = 1000, ...)

Arguments

np degree of polynomial surface
covmod function to evaluate covariance or correlation function
x x coordinates or a data frame with columns x, y, z
y y coordinates
z z coordinates. Will supersede x$z
nx Number of bins for table of the covariance. Increasing adds accuracy, and increases size of the object.
... parameters for covmod

Value

list with components

beta the coefficients
x
y
z and others for internal use only.

See Also

trmat, surf.ls, prmat, semat, expcov, gaucov, sphercov

Examples

data(topo, package="MASS")
topo.kr <- surf.gls(2, expcov, topo, d=0.7)
trsurf <- trmat(topo.kr, 0, 6.5, 0, 6.5, 50)
contour(trsurf)
prsurf <- prmat(topo.kr, 0, 6.5, 0, 6.5, 50)
contour(prsurf, levels=seq(700, 925, 25))
sesurf <- semat(topo.kr, 0, 6.5, 0, 6.5, 30)
contour(sesurf, levels=c(22,25))

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