spatial clusters

Dear Roger,

Thanks, your suggestions was helpful. I think I exaggerated the questions,
but for all countries:  ?Error in mstree(le, 5): Graph is not
connected!?; taking only some samples of countries the graph is
connected. There is something to be done in this case?

All the best,
Dorina



On Tue, 21 Dec 2010 09:40:35 +0100 (CET), Roger Bivand
<Roger.Bivand at nhh.no> wrote:

On Mon, 20 Dec 2010, dorina.lazar wrote:

Dear all,

Finally, with your help, I make some progress to apply SKATER algorithm
to
European countries.

Here is the R code, following the example from  spdep package pdf:

country<-wrld_simpl[wrld_simpl$ISO3%in%c("AZE", "ALB", "ARM", "BIH",

"BGR", "CYP", "DNK", "IRL", "EST", "AUT", "CZE", "FIN",  "FRA", "GEO",
"DEU", "GRC", "HRV", "HUN", "ISL", "ITA", "LVA", "BLR", "LTU", "SVK",
"LIE", "MLT", "BEL", "AND",  "LUX", "MCO", "NLD", "NOR", "POL", "PRT",
"ROU", "MDA", "RUS", "SVN"),]

ske<-spCbind(country, rclasif)
ske at data
de <- data.frame(scale(ske at data[13]))   #col 13 contains the health

indicator (from rclasif)

nbe <- poly2nb(country)
ce <- nbcosts(nbe, de)
le <- nb2listw(nbe, ce, style="B", zero.policy=TRUE)

Error in nb2listw(nbe, ce, style = "B", zero.policy = TRUE) :
neighbours and glist do not conform

Using your corrected list of countries, I see two/three problems:

1) some proximate polygons do not touch because of line generalisation

in

the simplification of the country polygons, use:

nbe <- poly2nb(country, snap=0.1)

to force neighbours to touch.

2) you are left with three real islands - Iceland, Cyprus, and Malta. To

join them in, consider:

knn4 <- knn2nb(knearneigh(crds, 4, longlat=TRUE),
   row.names=row.names(country))
knn4s <- make.sym.nb(knn4)
nbe1 <- union.nb(nbe, knn4s)

3) nbcosts() does not like single-column data frames, as it is supposed

to

be for multivariate data, so:

de <- data.frame(rnorm(46))
ce <- nbcosts(nbe1, de)
which(sapply(ce, function(x) isTRUE(any(is.na(x)))))

gives an NA at the end of each line of cost distances, but:

de <- data.frame(rnorm(46), rnorm(46))
ce <- nbcosts(nbe1, de)
which(sapply(ce, function(x) isTRUE(any(is.na(x)))))
le <- nb2listw(nbe1, ce, style="B")

doesn't, nor does:

de <- data.frame(rnorm(46), rep(1, 46))
ce <- nbcosts(nbe1, de)
which(sapply(ce, function(x) isTRUE(any(is.na(x)))))
le <- nb2listw(nbe1, ce, style="B")

From there,

mst.bh <- mstree(le,5)
res1 <- skater(mst.bh[,1:2], de, 2)
plot(country, col=heat.colors(3)[res1$groups])

seem to work.

I think that it makes sense for nbcosts() to fail for non-connected
observations, but perhaps it should explain why.

Hope this helps,

Roger

I mention that:
-	at "nbe", appears the message:  6 regions with no links: CYP DNK HRV
ISL
MLT SWE
-	"ce" contain a lot of NA
If you have some ideas about the cause of this Error, please help me to
finalize my exercise on SKATER algoritm.

Thanks a lot for your help,
Dorina




On Sat, 18 Dec 2010 18:42:35 +0100 (CET), Roger Bivand
<Roger.Bivand at nhh.no> wrote:

On Sat, 18 Dec 2010, Roman Lu?trik wrote:

Perhaps you could follow the instructions from this

exchange<http://r-sig-geo.2731867.n2.nabble.com/Guam-island-map-td4969467.html#a4972725>and

see if you can extract the desired country (assuming the resolution
suits you).

I don't think that we know which countries Dorina needs, or at which
administrative level. If there are only 30 country observations, and

the

countries are not contiguous, then the whole exercise seems

unnecessary.

Can Dorina use the simplified world map in the maptools package:

library(maptools)
?wrld_simpl

adding the data using the ISO country names? If these are countries at
some administrative division level, then maybe www.gadm.org will have

what

is needed, but the countries will have to be joined together, or the

whole

map subsetted. If these are say EU NUTS2 regions, then use can be made

of

GISCO shapefiles from Eurostat. But we don't know what boundaries are
needed, and of course to use Skater for clustering, you need the
boundaries.

Roger

Cheers,
Roman



On Sat, Dec 18, 2010 at 6:20 PM, Dorina Lazar <drnlazar at yahoo.com>

wrote:

Georg,

Thanks for being very patient with me.

I have not a shapefile for countries.

I have tried to obtain it. I have loaded a shapefile for Finland,

GIS

data,
from

http://www.eea.europa.eu/data-and-maps/data/eea-reference-grids/zipped-shape-file-finland

and I tried to read the file FI_1K.shp
Fin<- readShapePoly(system.file("etc/shapes/ FI_1K.shp",
package="spdep"))
but...
Error in getinfo.shape(filen) : Error opening SHP file

How can I obtain, for each country,  the shapefile spatial polygon

in

R

(SpatialPolygons-DataFrame)?

Thanks again,
Dorina


--- On Thu, 12/16/10, Georg Ru? <research at georgruss.de> wrote:

From: Georg Ru? <research at georgruss.de>
Subject: Re: [R-sig-Geo] spatial clusters
To: "Dorina Lazar" <dorina.lazar at econ.ubbcluj.ro>
Cc: "R-sig-geo mailing list" <r-sig-geo at r-project.org>
Date: Thursday, December 16, 2010, 10:41 AM
On 16/12/10 09:06:33, dorina.lazar
wrote:

How to create a shapefile including my data about some

socio-demographic

indicators (7),  for about 30 countries around

the world (to be read with

readShapePoly)?

Hi Dorina,

I'm not quite sure what you have and what you want.

I assume that you'd like to create a shapefile such that
for every country
(which is represented as a polygon) there's a vector of
seven attributes
attached to it:

country1:  attr1 attr2 attr3 attr4 attr5 attr6 attr7
country2:  attr1 attr2 attr3 attr4 attr5 attr6 attr7
...

Do you have your countries as spatial polygons in R
(SpatialPolygons-
DataFrame or similar)? If yes, you should be able to add
your socio-demo-
graphic indicators to this data frame (just as in normal
data frames). In
this way you'd join the data you have inside R.

If you have the shapefile for the countries available and
would like to
edit this directly to add the indicators, I'd suggest using
a GIS like
GRASS http://grass.fbk.eu/ Afterwards, this can be easily
read into R.

Would be useful to suggest some good introductory

lectures in spatial

statistics (links or books).

I think the following is what Roger would suggest:

 author = {Bivand, Roger S. and Pebesma, Edzer J. and
G?mez-Rubio, Virgilio},
 title = {Applied Spatial Data Analysis with R},
 series = {Use R},
 publisher = {Springer},

http://www.asdar-book.org/
http://www.springerlink.com/content/uw07v1/
(Depending on your login/institute you may have fulltext
access, but the
book is definitely worth buying anyway.)

Regards,
Georg.
--
Research Assistant
Otto-von-Guericke-Universit?t Magdeburg
research at georgruss.de
http://research.georgruss.de