Hi Edzer, thanks for the help,
i managed to use the predict() function now. But when I try to plot the
predictions using spplot() i get this error :
Error in parse(text = x) : text:1:3: unexpected symbol 1: 0.pred
Where 0.pred is the the prediction to plot.
Does anyone has any ideas to
...and attachement...
r, m
-Original Message-
From: r-sig-geo-boun...@r-project.org [mailto:r-sig-geo-boun...@r-project.org]
On Behalf Of Matevž Pavlič
Sent: Monday, July 18, 2011 8:47 AM
To: r-sig-geo@r-project.org
Subject: Re: [R-sig-Geo] predict() LDL error
Hi Edzer, thanks for the
Hi Caspar,
still get the same error. The str(z) shows this info :
str(z)
Formal class 'SpatialPixelsDataFrame' [package sp] with 7 slots
..@ data :'data.frame': 8736 obs. of 9 variables:
.. ..$ 0.pred : num [1:8736] 0.174 0.174 0.174 0.174 0.176 ...
.. ..$ 0.var : num
Hi,
thanks for the help. I renamed it to letters and it works perfectly now.
Thanks again for your time, m
From: caspar hallmann [mailto:caspar.hallm...@gmail.com]
Sent: Monday, July 18, 2011 9:44 AM
To: Matevž PavliÄ
Cc: r-sig-geo@r-project.org
Subject: Re: [R-sig-Geo] predict()
Hi,
I'm trying to plot some data (z) that is linked to latlong coordinates
(xy). These coordinates are not however on a regular grid. I also have some
shapefiles on which I would like to overlay the data. I can plot the
shapefiles (country/city outlines) and overplot the data, but
Hi to all,
I'm trying to use subs function, but I've an error when I use by=
with the name of the column. But if I use the column number it work:
subs(raster_cluster,data_6SV_cluster,by=1,which=2)
class : RasterLayer
dimensions : 55, 66, 3630 (nrow, ncol, ncell)
resolution :
On Thu, 14 Jul 2011, Kitty Lee wrote:
Hi. I have a shapefile. I guess because of cartography problem, the
border of some of the units that are supposed to be physically connected
are 'snapped' properly. As a result, when I use poly2nb, there are empty
links.
Did you notice on the help page
Hi all,
ok i managed to create a prediction with predict() (with gstat object).
However, what i get now is a set of predictions and covariances grids for each
class. Which is great of course, but what i would really like is to create a
map of these classes.
I suppose the maximum value of
I'm trying to use subs function, but I've an error when I use by=
with the name of the column. But if I use the column number it work:
colnames(data_6SV_cluster)
[1] cluster intercept coefficient
subs(raster_cluster,data_6SV_cluster,by=cluster,which=2)
Error in `[.data.frame`(y, ,
