[R-sig-Geo] Moran's I based on ZIP Code data

[Nikhil Kaza]

The national files for the zipcodes seems greyed out. I would caution  
against creating nb lists for each state separate and then creating a  
US wide neighbour list because, there will some zip codes in Alabama  
who are neighbours to  zipcodes in GA, MS, TN. I would merge them  
first into one big file and then construct the poly list.  you may run  
into memory issues for this operation, depending on your set up.


Nikhil Kaza
Asst. Professor,
City and Regional Planning
University of North Carolina

nikhil.list at gmail.com

On Aug 20, 2010, at 1:06 PM, Sharon O'Donnell wrote:

> Check out
>
> http://www2.census.gov/cgi-bin/shapefiles2009/national-files - left  
> hand
> side has national - level data.
>
> All 5 digit zipcode files are based on 2002 data but zipcode  
> boundaries
> change less frequently than tracts and blockgroups, there may be  
> some issues
> in correctly mapping out areas in high growth regions of the U.S.  
> with new
> zipcodes.
>
> Sharon
>
> On Fri, Aug 20, 2010 at 12:47 PM, Michael Haenlein
> <haenlein at escpeurope.eu>wrote:
>
>> Thanks very much for your reply, Roger!
>>
>> I have downloaded the shape files from the US Census ZCTA webpage.  
>> In case
>> anyone else is interested in obtaining them the URL is:
>> http://www.census.gov/geo/www/cob/z52000.html#shp
>>
>> I also managed to import those files into R and to convert them into
>> a neighbour list:
>>
>> Alabama <-readShapePoly("c:/111/zt01_d00")
>> Alaska <-readShapePoly("c:/111/zt02_d00")
>> Arizona <-readShapePoly("c:/111/zt04_d00")
>> ...
>>
>> Alabama.nb <- poly2nb(Alabama)
>> Alaska.nb <- poly2nb(Alaska)
>> Arizona.nb  <- poly2nb(Arizona)
>> ...
>>
>> The problem is that instead of having one neighbour list I now have  
>> 52 ones
>> (one for each state).
>> Is there a way to combine all of them into one large neighbour list  
>> which I
>> can then use as an input for my analysis?
>>
>>
>>
>>
>> -----Original Message-----
>> From: Roger Bivand [mailto:Roger.Bivand at nhh.no]
>> Sent: Thursday, August 19, 2010 23:54
>> To: Michael Haenlein
>> Cc: r-sig-geo at stat.math.ethz.ch
>> Subject: Re: [R-sig-Geo] Moran's I based on ZIP Code data
>>
>> On Thu, 19 Aug 2010, Michael Haenlein wrote:
>>
>> The first thing is to get the locations of the zip codes (about  
>> 30,000?) -
>> they are published as shapefiles by state (US Census ZCTA), so a  
>> polygon
>> representation is possible, but you could also look for a point
>> representation. Next make a neighbour list (nb) object to the zip  
>> code
>> entities for which you have observations. Then you could use  
>> nb2blocknb()
>> in
>> spdep to "block up" observations where more than one belongs to the  
>> same
>> zip
>> code, which effectively makes all the observations in a zip code
>> neighbours,
>> and adds all the observations in neighbouring zip codes too.
>> It was written for housing data with only a postcode but no geocoded
>> address.
>>
>> Hope this helps,
>>
>> Roger
>>
>>
>> --
>> Roger Bivand
>> Economic Geography Section, Department of Economics, Norwegian  
>> School of
>> Economics and Business Administration, Helleveien 30, N-5045 Bergen,
>> Norway.
>> voice: +47 55 95 93 55; fax +47 55 95 95 43
>> e-mail: Roger.Bivand at nhh.no
>>
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>>
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