Re: AI-GEOSTATS: Kriging Error vs variance

2003-01-27 Thread Digby Millikan


 Russell,
 If you have time to get to your library there is a book
"Geostatistical Ore Reserve Estimation" 1977 M.David 
although related to geostatistics for mining this book
is written by a renowned geostatistician and has an 
excellent diagrammatic representation of trend, drift
and stationarity Fig. 188, 189 pp267 which relates to 
 your question.

Hope this is of some help.

Thanks,

Regards Digby Millikan B.Eng

Geolite Mining Systems
U4/16 First Ave.,
Payneham South SA 5070
Australia.
Ph: +61 8 84312974

[EMAIL PROTECTED]
http://www.users.on.net/digbym


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Re: AI-GEOSTATS: Kriging Error vs variance

2003-01-27 Thread Digby Millikan
You may have to consider the stationarity of your data, i.e. theoretically
your sample mean is better than your kriged estimate if your kriginng error
is greater than your kriging variance, but you did make the assumption that
your data is stationary when you kriged it, i.e. constant mean and variance,
if this is not the case then you should consider this when adopting your
sample mean.

Regards Digby Millikan B.Eng

Geolite Mining Systems
U4/16 First Ave.,
Payneham South SA 5070
Australia.
Ph: +61 8 84312974

[EMAIL PROTECTED]
http://www.users.on.net/digbym


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Re: AI-GEOSTATS: Kriging Error vs variance

2003-01-27 Thread Pierre Goovaerts
Hi Russell,

I am assuming you refer to kriging error variance.

If your semivariogram is bounded and has a sill
close to the sample variance, then the simple kriging
estimate will automatically be the global mean
when the kriging variance is the sample variance
(that is when all observations are beyond the range
of spatial correlation). Note that you might
want to decluster your sample mean before using it as global mean.

For ordinary kriging, the kriging variance would actually
be greater than the sample variance because of the
Lagrangian parameter. I don't think I would adopt
a global/sample mean instead of the local mean provided
by ordinary kriging even if the variance of the
estimator is smaller.

However, for kriging with a trend or universal kriging,
I wouldn't trust too much the estimate obtained for
large kriging variance since the extrapolated trend
can be very unrealistic (e.g. negative concentration estimates).

Pierre
<><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><>

Dr. Pierre Goovaerts
President of PGeostat, LLC
Chief Scientist with Biomedware Inc.
710 Ridgemont Lane
Ann Arbor, Michigan, 48103-1535, U.S.A.

E-mail:  [EMAIL PROTECTED]
Phone:   (734) 668-9900
Fax: (734) 668-7788
http://alumni.engin.umich.edu/~goovaert/

<><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><><>

On Mon, 27 Jan 2003, Russell Barbour wrote:

> Dear List members,
> I am looking for a reference on interpretation of the Kriging error versus the
> sample variance. Am I correct in assumung that in any kriged interpolation
> where the Kriging error is greater than the sample varience then the sample
> mean would be a better estimate at that location?
>
> Thanks for your help
>
> Russell Barbour Ph.D.
> Research Associate in Applied Mathematics
> Vector Ecology Laboratory
> Yale School of Medicine
> 60 College St. Rm 600
> New Haven CT. 06520
> TEL: 203 785 3223
> FAX 203  785 3604
> email: [EMAIL PROTECTED]
>
>
>
>
> --
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>responses to your questions.
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>"unsubscribe ai-geostats" followed by "end" on the next line in the message body. DO 
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>


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Re: AI-GEOSTATS: Kriging Error vs variance

2003-01-27 Thread Isobel Clark
Russell

Absolutely on the spot.

We call this the 'ygiagam' criterion (your guess is as
good as mine) ;-)

Isobel Clark
http://geoecosse.bizland.com/news.html

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AI-GEOSTATS: Kriging Error vs variance

2003-01-27 Thread Russell Barbour
Dear List members,
I am looking for a reference on interpretation of the Kriging error versus the 
sample variance. Am I correct in assumung that in any kriged interpolation 
where the Kriging error is greater than the sample varience then the sample 
mean would be a better estimate at that location?

Thanks for your help 

Russell Barbour Ph.D.
Research Associate in Applied Mathematics
Vector Ecology Laboratory
Yale School of Medicine
60 College St. Rm 600
New Haven CT. 06520
TEL: 203 785 3223
FAX 203  785 3604
email: [EMAIL PROTECTED]




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