Dear Jeff,
I think you cannot escape discretizing your kriging surface as there is
no mathematical expression that captures the kriging surface. To use
optim you could make an objective function that was two inputs, x and y
location. The functions calls the fields package to estimate the kriging
prediction at this point and returns it. This ofcourse assumes that the
variogram model is known. You have to play with the settings of optim to
get it working and prevent a local minimum. You could take a look at
SANN (simulated anealing) which is part of optim.
cheers,
Paul
On 06/11/2010 07:24 AM, v v wrote:
Hi,
I am using the 'fields' package to conduct Kriging interpolation on my dataset.
I have managed to generate the 3-dimensional surface plot of the Krige-fitted
surface. There are several local minima points on the surface. My main interest
is to pinpoint the exact x-y coordinates of the lowest response (elevation)
point of each of the local minima points.
Although an approximation is possible by generating predicted values using a
regularly-spaced grids, such approximations are not good enough for my
purposes. I have intentions to use the optim() and/or constrOptim() functions
to locate the minima but I do not know what is the objective function to be
optimized. Therefore, so far, I am still unable to do that.
So, know how can I locate the local minima on a Krige-fitted surface?
regards,
Jeff Yeo
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