Hello Peter
For that regard the definition of nugget effect you can read a good
explanation in "statistics for spatial data"(author Noel A. C. Cressie).
I think that you can find there all you need.
Sebastiano Trevisani
Ph.D. Padova University
I
At 01:48 PM 8/19/2003 +0200, Peter
You can also try to work with some transform of your data (logarithmic for
example). And if you have many data you can try to use an indicator
approach. The code SADA could be useful for study your data set.
Sebastiano Trevisani
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is method works well with almost
exhaustive data set but not when you have few data and the problem is
complex (often in geostatistics).
What do you think?
Thank you in advance
Sebastiano Trevisani
Ph.D Padova University Italy
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Hi!
There is something about negative weights in "geostatistics for natural
Resources Evaluation" of Pierre Goovaerts. Also in Srivastava's
"Applied geostatistics" you can find something of useful.
Sebastiano
At 05:29 PM 9/4/2003 +0200, [EMAIL PROTECTED] wrote:
Hi Mailinglist!!!
I have go
weights in the kriging matrix (as I
can see looking at the debug file). Now I'm wondering how (if it is
possible) I can use this estimation variance.
Or better: in which way I can interpret this estimation variance?
Thank you in advance for your help...
Sebastiano Trevisani
Ph. D. student --Ge
Dear Isobel Clark
Thank you very for your help
I have used the software on your web site and I have understood more
precisely in which way kriging estimation variance works
Sincerely
Sebastiano Trevisani
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* As a general
HI list members!
Some one of you know if there is some way to get Gslib fortran 90 source
code (not fortran 77)?
Thank you in advance
Bye
Sebastiano Trevisani
Padova University
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where to look thank you for your help!
Sebastiano Trevisani
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reholes, I can geometrically discretize the
boreholes in data to use in simulation or estimation.
For example I divided a borehole of 10m in punctual values spaced every
25cmbut probably it is not the best approach.
Sincerely
Sebas
c for Natural Resources Evaluation chapter 6 could give you an
hand. Gstat code permit you easily to perform kriging with extrernal
drift.
Sincerely
Sebastiano Trevisani
At 04:35 PM 11/27/2003 +0100, Sigrun kvarno wrote:
Dear AI-GEOSTATS
members,
I tried co-kriging for the first time yesterday, an
Maybe, in order to have a quick and "safe" interpolation, the natural neighbor
method of Dave Watson could perfom better than TIN.
Sebastiano Trevisani
Quoting Gregoire Dubois <[EMAIL PROTECTED]>:
> Dear list,
>
> I would appreciate feedback on an issue that is clo
Well, Simone in my Ph.D thesis (available online, see geostatistics in other
language on ai-geostats web site)I tried to explain it in a simple way...
Bye
S. Trevisani
Scrive Simone Sammartino <[EMAIL PROTECTED]>:
> Dear all
> about Irf-k...
> I can't understand the link between the two approach
) that you can not
one time calculate trend globally and the other time locally: it could happen
that globally you need a quadratic trend while locally a linear trend model is
enough. What about that?
Sincerely,
Sebastiano Trevisani
At 03.48 07/07/2005, [EMAIL PROTECTED] wrote:
Hi all
I may
case that kriging is
wrong, geostatistics (or if you want spatial statistics...) will be
still alive...
and really useful.
Sincerely
Sebastiano Trevisani
At 19.13 01/06/2006, JW wrote:
Hello Tom,
Thanks for making my case against geostatistics even more
compelling. Just assume, krige, mod
Dear List Members
I'm trying to find some paper explaining relationship and differences
between classical geostatistical methodologies
and objective analysis.
I'm working with oceanographic data set (really complex: the data are
4D) it seem that in the oceanography world objective analysis
Dear list
I would like also to suggest another point:
really often there is a relationship between
topographic elevation and hydraulic head
data values; in this case an external drift approach could be useful.
Bye
Sebastiano
At 20.16 20/08/2006, Edzer J. Pebesma wrote:
Hi all,
I agree with
Hi Bob
Thank you for the useful references
I forgot to mention the fact that sometime when you detrend hydraulic
head data using topography it could happen that the remaining
residuals show a pure nugget effect (i.e. all the spatial continuity
is described by the trend).
Then, (do you agree
Dear list member
A procedural question for you...
I'm thinking to transform my data in a standardized anomaly [i.e.
(raw datum- sample average)/sample standard deviation)] and then I`ll
perfom the geostatistical analysis on these transformed data. At
first glance, I don't see problem in t
ation also assumes that your data follow a
fairly symmetrical histogram.
Your semi-variogram will look exaclty the same as your 'raw' data
semi-variogram but should have a sill around 1.
Isobel
http://www.kriging.com
Sebastiano Trevisani <[EMAIL PROTECTED]>
wrote:
Dear list me
Hi Isobel
Yes, the standardization is made for each layer separately (and so the
back transformation).
Actually I'm going to calculate the anomalies...and then let's see!
In this case I'm lucky because of the sampling along Z is regular.
Sincerely
Sebastiano
At 12.46 28/08/2006, Isobel Clark wrot
repeated until all your layers have
vertical variograms with no drift and therefore you have split your data
correctly.
Hope this helps
Regards
Bill Northrop
-Original Message-
From: [EMAIL PROTECTED]
[
mailto:[EMAIL PROTECTED]]On Behalf Of sebastiano
trevisani
Sent: Monday, August
-Original Message-
From: sebastiano trevisani
[
mailto:[EMAIL PROTECTED]]
Sent: Monday, August 28, 2006 2:06 PM
To: Bill Northrop
Cc: ai-geostats@jrc.it
Subject: RE: AI-GEOSTATS: Re: standardized anomaly
Hi Bill
Thank you for your mail.
In my case of study there are not sharp bounda
e to be a party pooper... :-( So, after trying to spoil
your joy, let me ask what about applying a logarithm, if the data are
positive? and we may follow the discussion prompted by Gregoire ;-)
Raimon
En/na sebastiano trevisani ha escrit:
> Hi Bill
> Yes, my idea is to conduct interpola
Dear list member
I' m wondering if in the case of negatively skewed data the rank
transformation is the best way to handle the problem.
As obvious my doubts are related to the back-transformation process.
Sebastiano
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+ To unsubsc
Dear list members
A technical question.
I got a problem using gstat inside R. When trying variogram
calculation I got the following message:
"dimensions do not match: locations 15882 and data 4749"
At first glance this error seems related to the presence of missing
values in my data (that
Hi
Maybe you can give a look to the book :
"Deutsch C V., Geostatistical Reservoir
Modeling: Oxford University Press, New York, 2002, 376 pp."
Sebastiano
At 15.55 16/01/2007, Rühaak, Wolfram wrote:
Dear all,
I would like to ask for some advice regarding a
simulation I am planning to compute
Hi
From what I remember there are many works of Journel.
As a personal consideration, I Have the fealing that more the
statistical spatial index is complex, higher is the probability
that we met non stationarity conditionsand so the inference from
data become quite difficult!
Sebastiano
At
Hi
I'm not sure to understand what you mean when you say kriging on non
planar surface.
If you are saying that you need to interpolate on to an irregular
grid, both GSLIB and GSTAT (and so R) permit
you to interpolate whatever set of points.
Bye
Sebastiano T.
At 03.14 03/04/2007, Olumide wr
which account for topography between the points). He
is currently on hoildays, but he may have ideas about that.
ciao, Peter
sebastiano trevisani <[EMAIL PROTECTED]> writes:
>Hi
>
>I'm not sure to understand what you mean when you say kriging on non
>planar surface.
>If
Hi
If you have many data (as I guess you have, given the way in which
you collected the data)
you can code the data by means of an indicator approach (as reported by Bob)
and apply a moving windows approach to calculate inside each window
the proportion
(well, it is like a probability of occur
Dear list member
I was working with gslib library and I had some troubles in trying to
interpolate with a linear variogram
(well, a power model with exponent = 1) and a nugget effect. In
particular both vmodel.exe as well as kt3d.exe don't
care about the value of the nugget effect imposed.
So
; />
UK you have to get the variogram of residuals!
It can be suspicious in some cases, then it is
preferable to use IRF-K approach.
Dr. Adrian Martínez Vargas
Departamento de Geología
ISMM, Las Coloradas s/n
Moa, Holguín
Cuba
CP 83329
-----Original Message-
From: sebastiano trev
Dear Syed, I opted for this solution for several reasons:
1) the slope of the model follows an experimental variogram.
2) I can filter the nugget effect.
3) Also with a linear variogram Kriging gives weights to
data taking into account distance as well as clustering (from this
perspective is rea
or any information about the session. The details of the session are
attached below or follow the link:
http://meetingorganizer.copernicus.org/EGU2016/session/20486
Sincerely,
Sebastiano Trevisani
Session: SSS12.11/GM2.4
*Learning from spatial data: representation, inference and modelling in
earth an
or any information about the session. The details of the session are
attached below or follow the link:
http://meetingorganizer.copernicus.org/EGU2016/session/20486
Sincerely,
Sebastiano Trevisani
Session: SSS12.11/GM2.4
*Learning from spatial data: representation, inference and modelling in
earth an
ttp://meetingorganizer.copernicus.org/EGU2016/session/20486>
Thank for your patience and kind regards!
Sebastiano Trevisani
* Sebastiano Trevisani, Ph.D.*
*Assistant Professor*
*Applied and Environmental Geology*
*IUAV University of Venice: www.iuav.it <http://ww
follow the link:
*http://meetingorganizer.copernicus.org/EGU2016/session/20486*
<http://meetingorganizer.copernicus.org/EGU2016/session/20486>
Thank for your patience and happy new year!
* Sebastiano Trevisani, Ph.D.*
*Assistant Professor*
*Applied and Environmental G
,
The Conveners
* Sebastiano Trevisani, Ph.D.*
*Assistant Professor*
*Applied and Environmental Geology*
*IUAV University of Venice: www.iuav.it <http://www.iuav.it/>*
*Address: Dorsoduro 2206, Venice 30123, Italy Tel:+39. 041. 257
1299Mail:strevis...@iuav.it
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