Seumas,
I was probably a bit misleading to say regression
is not an estimation technique. The word regression
meaning to revert back to the original, or find the
underlying real equation for a set of data. Kriging
is a form of what is called generalised linear regression
which is one of the
For ore resource modelling I've used IDW on a highly skewed lognormally
distributed deposit, where no variograms could be produced. With lognormally
distributed data often found in ore resources, having a good variogram is
important, to avoid large errors in kriging hence it may be preferential to
: Tue 1/4/2005 3:06 PM
To: ai-geostats@unil.ch
Cc:
Subject: RE: [ai-geostats] Regression vs. Kriging vs. Simulation vs. IDW
Just to get the group's opinion on this -
When do you use IDW? When is it an advantageous technique
Darla Munroe wrote:
Just to get the group's opinion on this -
When do you use IDW? When is it an advantageous technique, or what purposes
does it well serve?
I use IDW to plot a smooth surface, fitted through the data points.
This may serve as another spatial visualisation of the data; I see
it
When comparing kriging versus regression, I meant
using linear regression between sparse and exhaustive
datasets to interpolate the sparse one, since as Digbi
Milligan pointed out in general case regression is not
an estimation method.
--- Gali Sirkis [EMAIL PROTECTED] wrote:
Seumas,
see
]; ai-geostats@unil.ch
Sent: Monday, January 03, 2005 12:34
Subject: RE: [ai-geostats] Regression vs. Kriging vs. Simulation vs. IDW
| Hi Seumas:
|
| I thought I would throw my 2 cents in regarding a comparison between
kriging
| and linear regression.
|
| While some of the responses have hit a few
Seumas,
see few practical points that you may find useful:
1. kriging vs regression:
a) kriging honors original data points, while
regression does not
b) kriging allows to account for anizotropy
c) kriging allows to control the influence of the data
points
2. Kriging versus other
Seumas
Linear regression : not really an estimation technique for spatial data,
though regression forms some of the basic
theory
for the derivation of kriging equations.
Splines: not really an estimation technique, just
Seumas,
Linear regression : not really an estimation technique for spatial data,
though regression forms some of the basic
theory for the derivation of kriging equations.
Splines : not really an estimation technique, just
Hi:
We had participated in AI-GEOSTATS SIC 2004 exercise in the past September.
I think that several techniques (Kriging, regression, etc.) may have been
used by different participants. It will be illuminating to read the final
report of SIC 2004 when available.
K.K. (Benjamin) Fang
(We had
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