[R-sig-Geo] Kriging with uncertain data

[Santiago Beguería]

Dear R-sig-geo list members,

I am curious about what are sensible approaches to spatial interpolation, most especially by using kriging, in the context of uncertain data.

Suppose one has a dataset of values observed at different locations, and each value consists on the expected value and its variance. Variance here represents the uncertainty related to the observation, and shows spatial variation due to external factors, for instance the geological setting affecting the quality of the measurement.

How would you proceed to model the spatial distribution of this variable, including propagation of the (spatially varying)?

I suppose one approach could be by simulation, but at there other ways of propagating the uncertainty that do not involve potentially expensive (in computation time) simulation approaches?

Cheers,

Santiago Beguería
CSIC
Spain