R: Evaluate Kriging Standard Error of Prediction over a Grid

semat {spatial}

R Documentation

Evaluate Kriging Standard Error of Prediction over a Grid

Description

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.

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))

[Package spatial version 7.3-17 Index]