How is kriging least square error?
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Why must data be transformed to normal for kriging, is it
that the mean
of mean of transformed data is a better estimate of the true
mean, i.e.
why is log estimate of mean a better estimate of the mean
than the raw mean
of logarithmic data?
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Do stationary hypothesis variograms have a sill,
and intrisic hypothesis variograms have no sill.
Does this mean intrisic hypothesis variograms
indicate a trend.
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Hello,
I was wondering about some variogram models not having a
sill.
Does this mean that semi-variogram values can be greater
than
the population variance, in which case you would have
negative
covariances, or is the population variance the maximum these
models, e.g. linear model, may reach.
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Hello,
I was wondering about some variogram models not having a
sill.
Does this mean that semi-variogram values can be greater
than
the population variance, in which case you would have
negative
covariances, or is the population variance the maximum these
models, e.g. linear model, may reach.
+
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Signoff ai-geostats
r) samples, lower variance in the larger
(shovel) samples).
Cheers
Richard Hague
- Original Message -
>Digby Millikan <[EMAIL PROTECTED]>
>To: ai-geostats , Kevin Lowe (Office
Park)><[EMAIL PROTECTED]>
>Subject: Re: [ai-geostats] Treatment of gold outliers
his helps.
Richard Hague
Original Message:
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From: Noemi Barabas [EMAIL PROTECTED]
Date: Mon, 8 Mar 2004 18:18:55 -0500 (EST)
To: [EMAIL PROTECTED]
Subject: AI-GEOSTATS: mysterious kriging output
Dear list,
I am working on a kriging problem of log-PCB concentrations in
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