Hi Simone... one way to look at it is to call Z(x) the tail variable and Z(x+h)
the head variable.
These are two variables describing the relative position in space of values of
the same physical
attribute. Then, you have your 2 variables to compute the covariance fuction
for a given vector h...
By pooling together pairs of data from different parts of the study area, you
are ignoring the
location x and simply using the length (and possibly orientation) of the vector
joining these 2 data...
which requires the assumption of stationarity of the covariance..
Hope it helps,
Pierre
-----Original Message-----
From: Simone Sammartino [mailto:[EMAIL PROTECTED]
Sent: Mon 5/2/2005 10:14 AM
To: Geostat newsgroup
Cc:
Subject: [ai-geostats] A banal question...
Dear all
a banal question...
I'm not able to understand the stationarity of covariance in second
order stationarity theory...
On any book or article I can read:
....covariance between Z(x) e Z(x+h) exist and does not depend on x,
but only on h; in fact
Cov[Z(x),Z(x+h)]=Cov(h)....
It is considered so banal that in any text I consulted this part is
described with the same sentence...but it is not explicated via mathematical
formalism....
Why should E[Z(x)Z(x+h)]-m^2 be so logically reduced to Cov(h)
You'll laugh for my request, but I'm not able to understand why it
should be so logical....
In some text I found also...=Cov(x1-x2)=Cov(h) where distance between
x1 and x2 is exactly h, but it does not help me to understand it....
I can't realize how to calculate Cov(h) that is a variable (it is in
reality at least a vector of constant), when usually covariance is calculated
between two variables....
Please have the patience to help me to solve this trick
Thanks
Simone
-----------------------------
Dr. Simone Sammartino
PhD student
- Geostatistical analyst
- G.I.S. mapping
I.A.M.C. - C.N.R.
Geomare-Sud section
Port of Naples - Naples
[EMAIL PROTECTED]
-----------------------------
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