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
On Montag, 28. August 2006 07:42 schrieb [EMAIL PROTECTED]:
> Do stationary hypothesis variograms have a sill,
Yes, variograms of weakly stationary random fields have a sill: the variance
of the field.
> and intrisic hypothesis variograms have no sill.
They might have no sill, but they also m
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
Good
morning Sebastiano,
I
found your problem interesting and I thought I would respond in this fashion. I
have done quite a bit of research on similar layered databases on fluvial
mineral deposits and found that if one did vertical (at right angles to the
contacts of the layers) variograms
Digby Some simplistic definitions which might help: (o) "stationary" implies that every location in the study area has a potential statistical distribution with the same mean and standard deviation. That is, all your samples come from the same distribution. (o) "intrinsic hypothesis" im
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
Hi Bill
Thank you for your mail.
In my case of study there are not sharp boundaries (or at least it seems
so!) but there is a gradual and fast decrease in horizontal spatial
variability going in depth.
Sincerely
Sebastiano
At 12.48 28/08/2006, you wrote:
Good morning Sebastiano,
I found your pr
Thanks for your replies - I am now trying to get access to the
mentioned papers, which may well be an even rougher quest.
Best Regards,
Nelson
On 8/25/06, Raimon Tolosana <[EMAIL PROTECTED]> wrote:
Hello, list
just a short comment: recall that sines and cosines are bound to sum
to one once squ
Hullo
Sebastiano,
It
sounds as if the Isobel's suggestion of a limited 3D search is the best
solution.
The
resultant models per layer should tell you if your approach has been correct,
especially if you do a trial run with an anisotropic model and search first to
see what spatial patte
Hi Bill
Yes, my idea is to conduct interpolations along layers (well, performing
a "tricky" 3D interpolation only to speed up the process).
Well, I'll already know that the shape and the range of the horizontal
variograms along Z doesn't change too much. I have some
doubt about anisotropy ...but
Dear list members,
searching the archive of the list and the web, I have difficulties to get an
access to suitable methods for the following problem:
I have simulations of a Monte Carlo radiative transfer model, where the path of
photons is tracked inside an atmospheric volume. I stored a horizo
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