Before I Kriged with a pure nugget variogram I would ask:
1. How many data points?
2. Do you expect the data to be spatially uncorrelated? (i.e. whatÂ’s
that variable?)
3. If you transform distribution to approximate normal is variogram
still pure nugget?
4. Does regression o
Mehari
SURFER will be giving you the arithmetic mean of the samples which fall
inside your search radius, not all possible samples. Effectively, you are
getting a "moving average".
Isobel
http://www.kriging.com
TED] [mailto:[EMAIL PROTECTED] On
Behalf Of Edzer J. Pebesma
Sent: 02 January 2007 16:28
To: Isobel Clark
Cc: Mehari Tekeste; ai-geostats@jrc.it
Subject: Re: AI-GEOSTATS: Re: Kriging using Nugget Model
For block kriging yes, for point kriging the prediction (standard) error
will be close to sigm
il: [EMAIL PROTECTED]
Web: http://www.nuigalway.ie/geography/gis
-Original Message-
From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] On
Behalf Of Edzer J. Pebesma
Sent: 02 January 2007 16:28
To: Isobel Clark
Cc: Mehari Tekeste; ai-geostats@jrc.it
Subject: Re: AI-GEOSTATS: Re: Kriging using Nugg
For block kriging yes, for point kriging the prediction (standard) error
will be close to sigma.
And happy new year to everyone on ai-geostats!
--
Edzer
Isobel Clark wrote:
Mehari
If you use a semi-variogram which is just nugget, the kriging estimate
will be the arithmetic mean of the sampl
Mehari
If you use a semi-variogram which is just nugget, the kriging estimate will
be the arithmetic mean of the sample values and the standard error will be the
standard sigma/root n of classical statistics.
Isobel
Mehari Tekeste <[EMAIL PROTECTED]> wrote:
Can I get some suggestio
