[R-sig-Geo] spatial clusters

[dorina.lazar]

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 Luštrik 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
>>>>>>
>>>>>> _______________________________________________
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>>>>>> R-sig-Geo at r-project.org
>>>>>> https://stat.ethz.ch/mailman/listinfo/r-sig-geo
>>>>>>
>>>>>
>>>>>
>>>>>
>>>>>
>>>>> _______________________________________________
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>>>>>
>>>>
>>>>
>>>>
>>>>
>>