surf.gls {spatial}R Documentation

Fits a Trend Surface by Generalized Least-squares


Fits a trend surface by generalized least-squares.


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


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


list with components

beta the coefficients
z and others for internal use only.


Ripley, B. D. (1981) Spatial Statistics. Wiley.

Venables, W. N. and Ripley, B. D. (2002) Modern Applied Statistics with S. Fourth edition. Springer.

See Also

trmat,, prmat, semat, expcov, gaucov, sphercov


library(MASS)  # for eqscplot
data(topo, package="MASS") <- surf.gls(2, expcov, topo, d=0.7)
trsurf <- trmat(, 0, 6.5, 0, 6.5, 50)
eqscplot(trsurf, type = "n")
contour(trsurf, add = TRUE)

prsurf <- prmat(, 0, 6.5, 0, 6.5, 50)
contour(prsurf, levels=seq(700, 925, 25))
sesurf <- semat(, 0, 6.5, 0, 6.5, 30)
eqscplot(sesurf, type = "n")
contour(sesurf, levels = c(22, 25), add = TRUE)

[Package spatial version 7.2-14 Index]