RE: [ai-geostats] Transformation of zero values for kriging
- Hi Christian,
It looks like your data are rates and consist of a numerator and denominator. In this case, you cannot apply common geostatistical tools since the reliability of your observations will vary depending on the number of eggs you have sampled for each plant.
I am facing similar problems with cancer rates and have been using both Poisson kriging and binomial cokriging. A few papers are available on my webpage and I just submitted another paper that describes Poisson kriging in more details and provides the code to do the analysis. I would gladly share it with you once it is accepted, which should be very soon.
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From: Schlatter Christian [mailto:christian.schlatter@...]
Sent: Tue 10/25/2005 4:33 AM
Subject: [ai-geostats] Transformation of zero values for kriging
We were studying lepidopteran egg parasitism rates in a grid design (on 6 x 24 plants, totally 144) in the field. The idea was to detect influences in terms of directional dependencies of the parasitism rate (variograms), of base parasitism rate (nugget), and of "distance of the effects" (range).
Now egg parasitism rate was quite low and rare due to different problems (meteorological, area, test site, spraying in field, etc) so we have an average of 10-20 % of parasitized eggs (out of 144 points). For some non-spatial statistical testing this was more or less ok.
For the geostatistical work (I was thinking of universal kringing), the number of values is quite little. So I was thinking about transforming them by means of the exponential function (exp^zi), in order to get 144 values and to retransform the result.
Can I proceed in this way or am I completely on the wrong way with this approach?
Thank you very much for you attention.
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