Roger Bivand wrote:
> On Mon, 25 Jun 2007, Agustin Lobo wrote:
>
>> I've tried (among other things):
>>> limit1 <- read.shape("limit_PNSN2000.shp")
>> Shapefile type: Polygon, (5), # of Shapes: 2
>>> limit1poly <- Map2poly(limit1)
>>> limit1owin <- as(limit1poly,"owin")
>> Error in .classEnv(thi
On Mon, 25 Jun 2007, Agustin Lobo wrote:
I've tried (among other things):
limit1 <- read.shape("limit_PNSN2000.shp")
Shapefile type: Polygon, (5), # of Shapes: 2
limit1poly <- Map2poly(limit1)
limit1owin <- as(limit1poly,"owin")
Error in .classEnv(thisClass) : unable to find an environment
On Mon, 25 Jun 2007, Dan Putler wrote:
Thanks, Dan, I agree that the bandwidths are the problem here. Often the
image breaks settings are also very misleading for 2D density plots, so
one needs to take care, as you show.
Roger
Hi Zhi Jie,
Below are some changes to your code which should m
Dear Roger Bivand,Tim Keitt, and Dan Putler,
Thanks for your answers. I have tried density.ppp(spatstat) and
kernel2d(splancs), but the results are not very satisfied. I think there
should be a higher density in the blue part of the map in the attachment.
My dataset has been put in the attachmen
Hi Zhi Jie,
Below are some changes to your code which should make you much
happier. It does involve the use of the RColorBrewer package to
create a color palette that makes the plot a bit easier to see. As
you can guess, the size of the standard deviation given to
density.ppp was the probl
additional to the
X = as(X, "SpatialPixelsDataFrame")
etc. there's a helper function that toggles between them; try:
fullgrid(X) = TRUE
class(X)
fullgrid(X) = FALSE
class(X)
--
Edzer
Agustin Lobo wrote:
> I understand, but how do I convert between one type and the other?
> I've tried:
>
> x <-
I understand, but how do I convert between one type and the other?
I've tried:
x <- GDAL.open("C:/ALOBO/dipu2006/STLL_VEG2006/ESTRAT3_OBAC.tif")
ESTRAT3OBAC <- asSGDF_GROD(x, output.dim=c(118,189))
GDAL.close(x)
[EMAIL PROTECTED]@data==55537]<- NA
X <- ESTRAT3OBAC[seq(1,118,by=10),seq(1,189,by=10)
I've tried (among other things):
> limit1 <- read.shape("limit_PNSN2000.shp")
Shapefile type: Polygon, (5), # of Shapes: 2
> limit1poly <- Map2poly(limit1)
> limit1owin <- as(limit1poly,"owin")
Error in .classEnv(thisClass) : unable to find an environment containing
class "polylist"
> limit2
Roger Bivand wrote:
> It may also be worth asking on the PostGIS list whether you could upload
> your geometries to PostGIS and have GEOS do the measurement - if you have
> access to the software and experience with it. It may be that it can
> handle geographical coordinates.
>
I have to be
Not only to avoid NAs, but also to get approximately right sample size.
Stratified sampling does not take place based on strata defined by
attributes (map layers), but rather by dividing the area into square
blocks (strata) and randomly sample (n=1) from each block. That is why
the resulting sa
Have you had a look at package ks? It seems to do rather nice bivariate
kernels, and (I think) generalises to other dimensions.
Cheers
Rob
*** Want to know about Britain's birds? Try www.bto.org/birdfacts ***
Dr Rob Robinson, Senior Population Biologist
British Trust for Ornithology, The Nunner
Is it possible to compute them experimentally, by computing the variance
of the back-transformed simulations for each prediction location?
--
Edzer
Paulo Justiniano Ribeiro Jr wrote:
> Dear Giovanna
>
> For certain values of the Box-Cox transformation it is not possible to
> compute kriging varia
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