Why not use cross-validation to empirically determine which method
performs best for this dataset (in addition to asking if they are
better than a random draw)? Robert
2009/2/9 Tomislav Hengl :
>
> Dear Yong Li,
>
> I hope you will not mind me joining this interesting discussion.
>
> If there is
Dear Rainer,
This is how can you can do it with the raster package
# install.packages("raster", repos="http://R-Forge.R-project.org";)
require(raster)
# Try it for a few files first..
n <- 10
# create a list (or vector) of file names, e.g. :
fn <- list()
for (i in 1:n) { fn[i] <- paste('myfile'
Many thanks for the message, Edzer.
-Original Message-
From: Edzer Pebesma [mailto:edzer.pebe...@uni-muenster.de]
Sent: Monday, 9 February 2009 7:08 PM
To: Yong Li
Cc: r-sig-geo@stat.math.ethz.ch
Subject: Re: FW: [R-sig-Geo] Interpolcation option: IDW or OK?
Yong Li wrote:
> Hi Edzer,
>
On Mon, 9 Feb 2009, Tomislav Hengl wrote:
Dear Rainer,
This is of course possible in R, and can be done in several ways:
1) for example, you can derive the average value using the rowSums function:
maps$Nsum <- rowSums(m...@data, na.rm=T, dims=1)
maps$avg <- maps$Nsum/(length(names(meuse.g.
Dear Rainer,
This is of course possible in R, and can be done in several ways:
1) for example, you can derive the average value using the rowSums function:
> maps$Nsum <- rowSums(m...@data, na.rm=T, dims=1)
> maps$avg <- maps$Nsum/(length(names(meuse.g...@data))-1)
You could also loop the sd,
Hi
I have 25000 maps, generated by simulation predictions, covering the
same area, and would like to calculate some descriptive stats, like
mean, standard deviation, median, quartiles of all cells, to create a
"variability map".
Is there an easy way of doing this in R?
Thanks,
Rainer
--
Raine
Dear Yong Li,
I hope you will not mind me joining this interesting discussion.
If there is no evident spatial auto-correlation structure (pure nugget effect),
IDW/OK are as good
as randomly drawing a value from the global (normal) distribution. You can even
test this using
cross-validation! I
On Mon, 9 Feb 2009, Agustin Lobo wrote:
Hi!
The following error only occurs if the R (2.7.2) session is started
from a GRASS shell opened through the QGIS GRASS plugin in windows.
The error does not occur If R is started form its own icon
or by double click in the .RData object, but then the
Hi!
The following error only occurs if the R (2.7.2) session is started
from a GRASS shell opened through the QGIS GRASS plugin in windows.
The error does not occur If R is started form its own icon
or by double click in the .RData object, but then the spgrass6
package would not find the GRASS
Yong Li wrote:
Hi Edzer,
I would say the spatial structure is regarded not significant when c0/c0+c1 is
very much greater than 75%. In my case I used even distance intervals and
calculated c0/c0+c1 for log(OLSENP) greater than 85%. I knew this index
sometimes is very fragile, very much depend
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