Evaluate Kriging standard error of prediction over a grid.

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

Input:
obj           object returned by `surf.gls'
xl,xu,yl,yu   limits of the rectangle for grid
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.

Output:
list with components x, y and z suitable for  `contour'  and
`image'.     

See also:
`surf.gls',   `trmat',   `prmat'   

Examples:
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))