You already use the correct means of setting the output resolution: increasing the resolution of the grid you pass to newdata
. In regard to performance, the bottleneck is often not the output resolution, but the size of the input dataset. Have a look at the maxdist
and nmax
arguments of krige
, which can be passed to autoKrige
and will passed on. These limit the number of points used in prediction, i.e. limit the size of the covariance matrix that needs to be inverted. Setting nmax
to, say, 100 should help with performance.
In regard to your second question. You can use multiple cores only in the sense to be able to run multiple autoKrige
analyses next to each other. automap
does not support parallel processing within one call to autoKrige
, and it would be quite a bit work to get that working. Have a look at the the parallel
package that comes standard with R, and the mclapply
function in that package.