Hi,

I am fairly new to R and gstat and kriging. However, I have been trying to
use gstat to carry out kriging on a set of heavy metal data that I have.
The heavy metal values are not normally distributed, however, a log
tranformation can get the data to be normal. There is also some correlation
between the heavy metal values and the distance from source of pollution of
the heavy metal (though it only explains 30% variation in the dataset).

I have carried out log normal ordinary kriging on the data (without taking
into account the correlation with distance from course). However, do you
suggest that it would be better to carry out regression kriging? In
addition, back transformation is an issue in my case, as I am interested in
the real values distribution of the heavy metal contaminant. Would you
suggest carrying out truncated gaussian kriging in this case?

Any suggestions would be much appreciated.

Thanks
Raz

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