ías
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-Mensaje original-
De: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] En nombre de Ashton Shortridge
Enviado el: 27 August 2008 22:22
Para: r-sig-geo@stat.math.ethz.ch
As
Hi Sarah,
This looks interesting and relevant:
http://www.leg.ufpr.br/mbgbook/
On Tuesday 26 August 2008, Edzer Pebesma wrote:
> Diggle & Ribeiro
--
Ashton Shortridge
Associate Professor [EMAIL PROTECTED]
Dept of Geography http://www.msu.edu/~ashton
2
Dave,
Transformation to a continuous distribution when the data follow a
discrete distribution is always messy, and the back-transform may get worse.
While you're at the library, try to pick up Diggle & Ribeiro's
Model-based geostatistics; they describe a model-based approach that
extends gl
Thanks Edzer,
I've requested Cressie's book from our library (just waiting on it).
My main concern was the many 0 counts. I also was not enthusiastic about
odd transformations which then require appropriate back-transforms (I
imagine the back transform of the kriging variance gets messy)
I've
Hi Dave,
Dave Depew wrote:
Hi all,
A question for the more experienced geostats users
I have a data set containing 2-3 variables relating to submerged plant
characteristics inferred from acoustic survey.
The distribution of the % cover variable is bounded (0-100) and highly
left skewed (m
Hi all,
A question for the more experienced geostats users
I have a data set containing 2-3 variables relating to submerged plant
characteristics inferred from acoustic survey.
The distribution of the % cover variable is bounded (0-100) and highly
left skewed (many 0's). The transect spacin
