Le 08/02/2018 à 20:16, Heinz a écrit :
Sorry, I am lost.
I have 10,000 xyz data and want to know, if there is some regularity in them
or if they are more or less random.
So you need and are speaking about the 3D autocorrelation of data(x,y,z).
Usually we compute it through a 3D convolution,

Hello,
There seems to be some statistical tests related to this, namely Moran’s
or Mantel tests :
https://stats.idre.ucla.edu/other/mult-pkg/faq/general/faq-how-can-i-detectaddress-spatial-autocorrelation-in-my-data/
http://www.petrkeil.com/?p=1050
hth
S.
Le 08/02/2018 à 20:16, Heinz a

1 The nearest neighbour distribution of N points in a 3d-Volume with
radius R is given by
W(r) = 1 - exp[ - N (r/r)^3] and this is a Weibull distribution and not a
Poisson distribution. The WIKI article, while correct, is a typical case
where high level statisticians are trying to make

You may want to study this article:
https://pdfs.semanticscholar.org/574f/8f7347a258f6431fb8316716ca51b9b7eacb.pdf
it should give you a clue or two of what you may want to implement.
-Original Message-
From: users [mailto:users-boun...@lists.scilab.org] On Behalf Of Heinz
Sent: Friday,

Looks interesting, but --uff-- difficult...
Thanks the lot
Heinz
-Original Message-
From: users [mailto:users-boun...@lists.scilab.org] On Behalf Of Rafael
Guerra
Sent: 09 February 2018 21:58
To: Users mailing list for Scilab
Subject: Re: [Scilab-users] spatial