R help - Jun 2003 - krige in gstat() package

HI,
  I wonder does anyone have experience with doing sequential gaussian
simulation with krige() function in gstat?

I find it VERY slow compared to use krige() to achieve kriging function
itself..  I wonder why, is that because it has to model the variogram, and
do the kriging separately for each point to be simulated?

so it would be N times slower to achieve the simulation than the kriging
if the number of points to be estimated is N??

Any hints is welcome and appreciated!
yan

> HI,
>   I wonder does anyone have experience with doing sequential gaussian
> simulation with krige() function in gstat?
>
> I find it VERY slow compared to use krige() to achieve kriging function
> itself..  I wonder why, is that because it has to model the variogram, and
> do the kriging separately for each point to be simulated?
It does not model variograms on the way. It is slower than kriging
because it uses the sequential simulation algorithm: for each node
visited, a value is simulated, and this value is added to the
conditioning data. For this reason you _have to_ limit the search
neighbourhood (using the nmax or maxdist arguments) if you're
simulating on more than say a few hundred nodes. Taking a very
small nmax may yield fast simulations, at the expense of a good
representation of the target spatial correlation structure.
> 
> so it would be N times slower to achieve the simulation than the kriging
> if the number of points to be estimated is N??
No. Experiment with the nmax argument.
--
Edzer