Re: Test data for (m-code) semiovariogram?

[Jose]

Hello.

I am also playing with spatial statistics.

On 06/22/2013 12:32 AM, fork wrote:
> https://gist.github.com/forkandwait/5834437
>
> It yields a similar but not exact empirical semiovariogram to the SAS example
> linked by UCLA, at least by looking at the graph (see below the coal data).
>
> Not sure how to interpret it with my real data (a home-rolled migration index
> by county), but I am working on it.

Short points from your code
- I could not find the "distmat" in my octave installation (3.6.4), 
neither with a quick search on Internet.
- Although it does not have significant importance, note that the data 
that you use in your test is not exactly the one from the UCLA web 
(check line 114).

I have also created my own script to calculate the semi-variogram.
https://gist.github.com/josombio/6871694

The main motivation was to learn, and to vectorize some parts to make it 
faster (I have large datasets).

Regarding the testing, I have the same problems than you, I am not 
completely sure about how to test it properly. I have added some simple 
tests, as you can see in the code (If you run the tests, a file with 
data will be downloaded automatically to your working directory and 
deleted after).

In particular I was also trying to reproduce as exactly as possible the 
figure from
http://www.ats.ucla.edu/stat/sas/faq/SAS_variogram_fit.htm
Note that it seems to be using a robust method (which is not specified 
in the page), not the classical one by Matheron. So in my search for a 
perfect match I also implemented some robust methods that I found in the 
literature, which still fail to reproduce the figure exactly. However, 
the figure from
http://www.ats.ucla.edu/stat/r/faq/variogram.htm
is well reproduced by my and your code (I used my own version of distmat).

If somebody has reference datasets (and results) with which I could test 
Cressie, N. and Hawkins, Genton and Dowd's robust methods, I would 
appreciate some links.

Regards
J.