Hi, Martin
Two years ago there was a similar discussion on the list:
http://markmail.org/message/tw7ulpxbgixieyys
If I understand it properly, your problem is you need to compute your variogram
using non-euclidian distances.
As far as I know, there is no package in R that can do so (correct me if
Dear list,
I just was wondering about sofware to perform 4D interpolations.
I've never tried and I'm probably not going to try it in the short time or but
I was asked to give (informal) advice about it and also I was curious.
I have heard GRASS gis can do that and also I've heard about EONFUSION
Dear Joe,
Maybe you could use a similar process that Marcelino suggested to me yesterday
in order to compute the shortest distance from points to a polyline.
You need to 1)convert your point data to ppp object in spatstat, 2)coerce your
polygon data to a psp object in spatstat.
3)nncross betwee
Telf.: (34) 971 401561
-Mensaje original-
De: r-sig-geo-boun...@stat.math.ethz.ch
[mailto:r-sig-geo-boun...@stat.math.ethz.ch] En nombre de Alex Mandel
Enviado el: 20 May 2009 14:33
CC: r-sig-geo@stat.math.ethz.ch
Asunto: Re: [R-sig-Geo] shortest distance from points to polylines
Pilar Tu
Hi list!
I need computing shortest distance from points to a polyline layer (coast line).
I've been searching all the morning a function in R that can do this but
couldn't find anything!
Is there any R function that do this? Or can anybody give me some hint about
how it could be done?
Kind rega
) 971 401561
-Mensaje original-
De: Virgilio Gomez Rubio [mailto:virgilio.go...@uclm.es]
Enviado el: 25 February 2009 09:44
Para: Paul Hiemstra
CC: Pilar Tugores Ferra; r-sig-geo@stat.math.ethz.ch
Asunto: Re: [R-sig-Geo] variance estimation (gstat, geoR, automap)
Hi,
In addition to the
Dear all,
I'm trying to estimate the variance of a global abundance estimation computed
by kriging interpolation and I am stuck.
One can easily retrieve the variance at each prediction location (either using
the package gstat, geoR or automap) using expressions similar to:
>kriging_object$kri
Hi Dave and everybody,
I also work with acoustic data collected in parallel equidistant transects(in
my case fish density)and we also have zero inflated data.
"Playing" with Arcgis I saw that performing a cell declustering previous to an
ordinary kriging improved substantially the predictions.
Hello everybody!
For sure it is very simple, but I can't find the way.
How could I obtain the numerical values of a experimental semivariogram or
variogram? Is it any function that makes this in geoR or gstat (or out of them)?
Thanks!
Pilar
Mª Pilar Tugores Ferrà
Becaria FPI - PhD Student
I would add Ordinary Least Squares (It may be the same as your SS), Weighted
Least Squares, Maximum Likelihood and Restricted Maximum Likelihood.
These four methods are available in the function likfit of the package geoR.
I've been using it a little bit and I think sometimes one method works bet
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