[R-sig-Geo] [R-sig-geo] quantify prediction variance by point with ordinary kriging

[Jessica Ruth Hullman]

Hi,

I'm still fairly new to kriging, and have been using ordinary kriging with
the gstat package on radon data from location in the north east US. I'm
basically using the method here to do this - 
http://casoilresource.lawr.ucdavis.edu/drupal/node/442
(create coordinates, then expand to grid, convert to gstat object, fit
variogram, update gstat object, then use predict() command, visualizing
with spplot()  

I'm creating kriging plots from a set of data sets, and then having people
estimate the radon value for each plot at a given location. It appears that
the kriging prediction variance sometimes causes the value shown on a plot
to fall in a different range (according to the legend) than the actual
value for that location in the input data set. I need to be able to
quantify exactly what the variance is (including direction) at my target
location by comparing the value from the output of the prediction (which I
understand is a SpatialPixelsDataFrame) to my value from the input data
set. 

I've been reading gstat documentation, but haven't been able to determine
the easiest way to do the translation I need to quantify variance by point.
Could anyone point me in the right direction? 

Thank you very much,

Jessica Hullman
Doctoral Candidate, Information Visualization
University of Michigan School of Information