Hi All,
I had a look at the paper suggested by Edzer. Some of my data is of
similar nature (% cover rather than direct counts; but many zeroes in
the data set). It is difficult to assess the presence of trends with
this variable due to 1) a limited number of covariates (i.e x,y, and
depth) but
Maybe this would be an appropriate time to mention
http://wiki.r-project.org/rwiki/doku.php?id=tips:spatial-data:when_to_use
How would list members answer this question?
David Hugh-Jones
PhD Candidate
Essex University Department of Government
http://davidhughjones.googlepages.com
2008/7/3 John
I agree. It's difficult to see any reason that someone who currently
uses R/GRASS would go to ESRI for spatial statistics. I come from a
long history as an ESRI user with an interest in spatial stats. As
others have said, ArcGIS may give you the basics quickly and easily, but
it is limited a
Paul,
Not to mention the huge cost of ESRI products and the fact that they run only
on the MS-Windows platform. R also integrates well with GRASS GIS. Personally,
I can not see any compelling reasons to go the ESRI route vs R/GRASS…
I feel a great debt of gratitude to the selfless developers of
Dear Hisaji,
I think that the choice of people for R is not only based on the fact
that a certain method is only available in R. R is much more flexible in
working with data, allows scripting, allows you to see exactly how a
method works, allows you to extend or develop methods and if you writ
Of course ESRI is trying to cover a wider field, as it has always done.
Quite a few versions ago they started with a geostatistical analyst,
which is used by many, but hasn't led to a decrease of interest in using
R for geostatistical purposes, is my impression. It has some very nice
features,
Hengl, T. wrote:
> I agree with Paulo - gstat can work with any linear model including the
> transforms of the original predictors e.g.:
>
> Z ~ X + X^2 + Y + Y^2etc.
>
> The problem is that gstat implements the so-called
> Kriging-with-external-trend algorithm to make predictions (see sectio
Hi list
(first post)
This new spatial analyst extension from ESRI looks promising and interesting.
Nice stuff.
I believe we use R and it's geographical abilities not only because it is robust and programmaticaly
efficient as well as an investment on ourself, but also because we do support open
Hi.
What do you think about ArcGIS 8.3's new statistical
functions(Calculation of spatial or network, GWR,
Global/Local Moran, Gi etc.) in its Spatial Analyst
Extension described in
http://webhelp.esri.com/arcgisdesktop/9.3/pdf/Whats_New_In_ArcGIS_93.pdf?
Current R's spdep's and spgwr's and oth
