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 |
y |
y coordinates |
z |
z coordinates. Will supersede |
nx |
Number of bins for table of the covariance. Increasing adds accuracy, and increases size of the object. |
... |
parameters for |
list with components
beta |
the coefficients |
x |
|
y |
|
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.
library(MASS) # for eqscplot 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) eqscplot(trsurf, type = "n") contour(trsurf, add = TRUE) 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) eqscplot(sesurf, type = "n") contour(sesurf, levels = c(22, 25), add = TRUE)
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