Albrecht Gebhardt
PVM Kriging with R
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Kriging is one of the most frequently used prediction methods in
spatial data analysis. This paper examines which steps of the
underlying algorithms can be performed in parallel on a PVM cluster.
It will be shown, that some properties of the so called kriging
equations can be used to improve the parallelized version of the
algorithm. The implementation is based on R and PVM (Parallel
Virtual Machine). An example will show the impact of different
parameter settings and cluster configurations on the computing
performance.