Hello dears
I have a spatial data set contaning n=262 observarion (The variable of interest is
Rate of Tuberculosis in 262 counties of Iran). I want to fit some models to
Directional semi-variograms,and then build anisotropic semi-variogram.
Then questions are
- Is there any rule for choosing
Are you using some kind of automated fitting?
The results would suggest that the model is
inappropriate or that your basic assumptions are
inappropriate. You should look at how the models are
being fitted and what assumptions are made and
question everything.
Isobel Clark
Andrew
You can apply 'standard' geostatistics if the
measurements are the 'average' (or some similar
feature) over an area.
It makes interpeting the semi-variogram extremely
tricky if you combine many different sizes of sample,
but common sense is the main thing here. The trick is
to derive a
Dear AI-GEOSTATiSticians,
My research is on heavy metal pollution in water bodies.
As a part of the analysis, I am doing kriging with the pollutant data.
I have couple of problems in doing this task.
1. Though I have the data sets for 90 water bodies, most of them (85) have
data points
less
My research is on heavy metal pollution in water
bodies.
Hi, some thoughts (your numbering):
(1) One of the things I have found successful is the
following:
construct your semi-variogram using ALL of your
data but not allowing pairs between samples in
different water bodies;
