

   EEvvaalluuaattee KKrriiggiinngg SSttaannddaarrdd EErrrroorr ooff PPrreeddiiccttiioonn oovveerr aa GGrriidd

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

   AArrgguummeennttss::

        obj: object returned by `surf.gls'

         xl: limits of the rectangle for grid

         xu:

         yl:

         yu:

          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 sup-
             plied.

   DDeessccrriippttiioonn::

        Evaluate Kriging standard error of prediction over a
        grid.

   VVaalluuee::

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

   SSeeee AAllssoo::

        `surf.gls', `trmat', `prmat'

   EExxaammpplleess::

        data(topo)
        topo.kr <- surf.gls(2, expcov, topo, d=0.7)
        prsurf <- prmat(topo.kr, 0, 6.5, 0, 6.5, 50)
        contour(prsurf$x, prsurf$y, prsurf$z, levels=seq(700, 925, 25))
        sesurf <- semat(topo.kr, 0, 6.5, 0, 6.5, 30)
        contour(sesurf$x, sesurf$y, sesurf$z, levels=c(22,25))

