--- Lucie Vallée <[EMAIL PROTECTED]>
wrote: >
>
> Could you explain what you mean by "nearest
> neighbour distances between samples locations"?
This is something I learned about in quantitative
ecology in the 1960's ;-)
You take each sample in turn and find the sample
closest to it. Note the d
Lucie, sorry I got this message when I tried to reply
to your e-mail. Hope you got the generic mailout.
> <[EMAIL PROTECTED]>:
> Connected to 192.77.51.5 but sender was rejected.
> Remote host said: 571
> This domain is banned.
Isobel
___
> 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;
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 tha
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 p
I have a question relating to this question, certainly not to question the
previous writer, it just seems like a good time to bring it up. Will
variograming and other such techniques work for the data the previous writer
described, e.g samples aren't at points, but areas (and areas that might
have
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
__
Think of it as focussing a camera. You are looking for
the clearest picture. There will be a certain lag (in
each direction) at which the calculation will balance
between detail on distance, detail on angles and
number of pairs.
In general:
# the more anisotropic the structure, the smaller the
t
Hello dears
I have a spatial data set containing n=262 observations (The variable of interest is
Rate of Tuberculosis in 262 counties of Iran). I have fitted exponential variogram
model to Empirical Directional Variogram, and I observed that the Estimated Range in
some directions is very very
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 L
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