RE: [ai-geostats] modelling trend and kriging type

Isobel Clark Thu, 07 Jul 2005 06:13:13 -0700

Perry

Your basic semi-variogram graph has a parabola added to it. Shoots off upwards (usually) at some distance. If the distance is large (past the range of influence) you can ignore it. See some of our mid-80s papers on the Wolfcamp data which lots of people use as a teaching set now. Or read my free tutorial at http://geoecosse.bizland.com/softwares (kriging with trend).

Isobel

[EMAIL PROTECTED] wrote:

Hi all

I may know this already, but what are the symptoms of data with a trend? What is the difference between a dataset with a trend and a non-stationary dataset?

Cheers

Perry Collier

Senior Mine Geologist
Ernest Henry Mine
Xstrata Copper Australia
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-----Original Message-----
From: Pierre Goovaerts [mailto:[EMAIL PROTECTED]]
Sent: Friday, 1 July 2005 12:54 AM
To: Recep kantarci; [email protected]
Subject: RE: [ai-geostats] modelling trend and kriging type

To add to the excellent comments by Edzer and Gregoire,

1. Universal kriging = kriging with a trend. The second terminology has been proposed by Andre
Journel who felt that the term "universal" was vague and misleadingly "ambitious".

2. Kriging with an external drift (KED) is mathematically the same as universal kriging (UK). Secondary variables
are simply replacing the spatial coordinates used in UK.

3. Regression kriging denotes all the techniques where the trend is modeled outside the kriging algorithm.
There are various methods that can be used to model that trend, ranging from linear regression
to neural networks. Kriging is used to interpolate the residuals. In practice these techniques have more
flexibility than universal kriging in term of modeling the trend: multiple variables either categorical or
continuous can be incorporated easily and many sofwtare are available for this trend modeling.
The only limitation is that the trend is modeled globally (i.e. the regression coefficients are constant
in space) while in KED the coefficients are reestimated within each search window.

Cheers,

Pierre

Pierre Goovaerts

Chief Scientist at Biomedware

516 North State Street

Ann Arbor, MI 48104

Voice: (734) 913-1098
Fax: (734) 913-2201

http://home.comcast.net/~goovaerts/

        -----Original Message-----
        From: Recep kantarci [mailto:[EMAIL PROTECTED]]
        Sent: Thu 6/30/2005 9:38 AM
        To: [email protected]
        Cc:
        Subject: [ai-geostats] modelling trend and kriging type


        Dear ai-geostats members

        When the data used has a trend, it is needed to model trend and in this case there exists various types of kriging to apply (universal kriging, kriging with a trend, regression kriging etc).

        If this is the case, does one should use the same type of kriging or different depending on modeling the trend using coordinates of target variable or using other (namely, secondary or auxillary) variables such as elevation or topography ? That is , are there a dinstinction depending on the type of variables to model the trend while kriging?


        Best regards
        Recep


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RE: [ai-geostats] modelling trend and kriging type

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