Evaluate Kriging Standard Error of Prediction over a Grid

Evaluate Kriging standard error of prediction over a grid.

Usage

semat(obj, xl, xu, yl, yu, n, se)

Arguments

obj

object returned by surf.gls

xl

limits of the rectangle for grid

xu

ditto

yl

ditto

yu

ditto

n

use n x n grid within the rectangle

se

standard error at distance zero as a multiple of the supplied covariance. Otherwise estimated, and it assumed that a correlation function was supplied.

Value

list with components x, y and z suitable for contour and image.

References

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

surf.gls, trmat, prmat

Examples

data(topo, package="MASS")
topo.kr <- surf.gls(2, expcov, topo, d=0.7)
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))