[R-sig-Geo] spatial clusters

dorina.lazar dorina.lazar at econ.ubbcluj.ro
Thu Dec 23 09:56:29 CET 2010 

Dear all,

Yes!!!   I succeed in my application related to SKATER algorithm; I begin
to find spatial statistics a very interesting field of research. 

Thanks a lot for your help, specially  to Roger and Georg.

I wish all of you A Merry Christmas and an Happy and Prosperous 2011! 
Dorina  


On Wed, 22 Dec 2010 13:16:55 +0100 (CET), Roger Bivand
<Roger.Bivand at nhh.no> wrote:
> On Wed, 22 Dec 2010, dorina.lazar wrote:
> 
>>
>> 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?
> 
> If I understand the approach used in SKATER correctly, there may only be

> one graph component, linking all the observations; check with:
> 
> n.comp.nb(nb)$nc
> 
> which I think must be 1. Otherwise it will not be able to divide the 
> (single) graph into clusters, because the input object imposes its own 
> subgraphs. Make sure that your samples meet the condition that:
> 
> n.comp.nb(nb)$nc == 1
> 
> Roger
> 
>>
>> 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
>>>>>>>>
>>>>>>>> _______________________________________________
>>>>>>>> R-sig-Geo mailing list
>>>>>>>> R-sig-Geo at r-project.org
>>>>>>>> https://stat.ethz.ch/mailman/listinfo/r-sig-geo
>>>>>>>>
>>>>>>>
>>>>>>>
>>>>>>>
>>>>>>>
>>>>>>> _______________________________________________
>>>>>>> R-sig-Geo mailing list
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>>>>>>>
>>>>>>
>>>>>>
>>>>>>
>>>>>>
>>>>
>>

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