been correct, especially if you do a trial run with an
anisotropic
>> model and search first to see what spatial pattern you obtain.
>> Will be interested to know what you get.
>>
>> Regards
>> Bill Northrop
>>
>> -----Original Message--
to see what spatial pattern you
obtain.
>> Will be interested to know what you get.
>>
>> Regards
>> Bill Northrop
>>
>> -Original Message-
>> From: sebastiano trevisani [
mailto:[EMAIL PROTECTED]]
>> Sent: Monday, August 28, 2006 2:0
o see what spatial pattern you obtain.>> Will be interested to know what you get.>> >> Regards>> Bill Northrop >>>> -Original Message->> From: sebastiano trevisani [ mailto:[EMAIL PROTECTED]>> Sent: Monday, August 28, 2006 2:06 PM>> To: Bill N
From: sebastiano trevisani [ mailto:[EMAIL PROTECTED]
Sent: Monday, August 28, 2006 2:06 PM
To: Bill Northrop
Cc: ai-geostats@jrc.it
Subject: RE: AI-GEOSTATS: Re: standardized anomaly
Hi Bill
Thank you for your mail.
In my case of study there are not sharp boundaries
: sebastiano trevisani
[mailto:[EMAIL PROTECTED]Sent: Monday, August 28,
2006 3:28 PMTo: Bill NorthropCc:
ai-geostats@jrc.itSubject: RE: AI-GEOSTATS: Re: standardized
anomaly Hi BillYes, my idea is to conduct
interpolations along layers (well, performing a "tricky" 3D interpolation
-Original Message-
From: sebastiano trevisani
[
mailto:[EMAIL PROTECTED]]
Sent: Monday, August 28, 2006 2:06 PM
To: Bill Northrop
Cc: ai-geostats@jrc.it
Subject: RE: AI-GEOSTATS: Re: standardized anomaly
Hi Bill
Thank you for your mail.
In my case of study there are not sharp bounda
throp
-Original Message-
From: [EMAIL PROTECTED] [
mailto:[EMAIL PROTECTED]]On Behalf Of sebastiano
trevisani
Sent: Monday, August 28, 2006 9:57 AM
To: Isobel Clark
Cc: ai-geostats@jrc.it
Subject: Re: AI-GEOSTATS: Re: standardized anomaly
Hi I
28, 2006 9:57 AM
To: Isobel Clark
Cc: ai-geostats@jrc.it
Subject: Re: AI-GEOSTATS: Re: standardized anomaly
Hi Isobel
I would like to use this transformation to deal with a 3D data set
characterized by a peculiarity (well, this is quite common!) in the
horizontal spatial variability.
In
Hi Isobel
Yes, the standardization is made for each layer separately (and so the
back transformation).
Actually I'm going to calculate the anomalies...and then let's see!
In this case I'm lucky because of the sampling along Z is regular.
Sincerely
Sebastiano
At 12.46 28/08/2006, Isobel Clark wrot
:[EMAIL PROTECTED]On Behalf Of sebastiano
trevisaniSent: Monday, August 28, 2006 9:57 AMTo: Isobel
ClarkCc: ai-geostats@jrc.itSubject: Re: AI-GEOSTATS: Re:
standardized anomaly Hi Isobel I would like to
use this transformation to deal with a 3D data set characterized by a
peculiarity
Sebastiano Your standardisation produces a mean of zero and a standard deviation of 1, without changing the characteristics of the semi-variogram (range, relative nugget effect etc.) I presume you will standardise each 'layer' separately? Then use a 3D search which does not include samples
Hi Isobel
I would like to use this transformation to deal with a 3D data set
characterized by a peculiarity (well, this is quite common!) in the
horizontal spatial variability.
In particular if I divide the dataset in horizontal layers I see that
horizontal variograms show a similar shape but w
Sebastiano You will be fine so long as you actually have a "stationary" phenomenon. That is, there is a constant mean and standard deviation over your study area -- no trends, no discontinuities, no changes of behaviour. Such a transformation also assumes that your data follow a fairly symmetri
13 matches
Mail list logo
