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| From | Joost Bruijsten <joostbruijsten@hotmail.com> |
| To | <statalist@hsphsun2.harvard.edu> |
| Subject | RE: st: spatgsa and converting coordinates from shp file |
| Date | Sun, 20 Jun 2010 13:10:47 +0000 |
Thank you for your answer. If I understand correctly, you wrote the spmap and spatgsa command Mr. Pisati? Do you consider taking the mean of the X en Y coordinates, which the shp2dta command create, as a good way to provide the different municipality their own two 'unique' coordinates? Best regards, Joost > Date: Sat, 19 Jun 2010 10:45:03 +0200 > From: maurizio.pisati@unimib.it > To: statalist@hsphsun2.harvard.edu > Subject: Re: st: spatgsa and converting coordinates from shp file > > The bandwidth for computing Moran's I should be set to any value that > makes sense to your research problem. In your case, coordinates appear > to be expressed in meters, so that option -band(0 10991) means that you > are defining the neighbors of every municipality j as the set of > municipalities whose centers are within a radius of 11 kilometers from > the center of j. If this definition doesn't suit your needs, than you > can extend the bandwidth the way you deem more appropriate to your > research problem. Likewise, choosing a binary or a non-binary spatial > weight matrix -- standardized or not -- depends on the way you want to > define spatial contiguity between municipalities (see related literature > for more info on spatial weight matrices). > Best wishes, > Maurizio Pisati > > > > > > > Il 19/06/10 10.06, Joost Bruijsten ha scritto: >> >> Dear Statalisters, >> >> my problem is about Moran's I (command: spatgsa) en the Weights matrix (spatwmat). >> >> I use Stata/SE 11.0 for Windows (32-bit). >> Born 21 October 2009 >> >> First of all, I am analyzing the urban structure of the Veneto region in Italy using commuting flows. >> I want to use Moran's I to see if employment is concentrated. Employment is defined in my study as the total number of working persons that commute into a region or municipality. >> >> Using shp files (from istat.it/ambiente/cartografia) I made the map of Veneto and the provinces and municipalities (using spmap). >> >> Then I took the coordinates that the spmap command uses (using shp2dta) of every municipality and used the mean of the x and y coordinates for every municipality in a new dataset with the total number of ingoing commuters into a municipality. Beneath you see an example I used. >> >> >> >> destinationprovince destinationmunicipality totalpersons x y >> >> 23 3 892 1630494 5007893 >> >> 23 8 686 1633549 5013109 >> >> 23 9 538 1641141 5030001 >> >> 23 10 489 1648422 5032311 >> >> 23 19 2463 1649542 5041687 >> >> 23 20 1882 1652473 5044176 >> >> 23 25 8405 1660123 5045447 >> >> 23 29 471 1662310 5047371 >> >> 23 44 15613 1667065 5051641 >> >> 23 48 1870 1668117 5052971 >> >> 23 72 1834 1668861 5053562 >> >> 23 85 676 1670068 5056730 >> >> 23 95 1607 1681036 5057435 >> >> I performed the commands for spatwmat and spatgsa (see beneath), although I changed the band width from a very high number (35000+) to the largest minimum distance the spatwmat command gave: >> >> spatwmat, name(test7) xcoord(x) ycoord(y) band(0 10991) >> >> My first question is: What is the best way with these sort of coordinates to set the band width? Or is there a way to convert these coordinates to real latitude and longitude variables? The last would actually be my preferred solution. >> >> I then used this command to calculate Moran's I: >> >> spatgsa totalpersons, weights(test7) moran >> >> This gave me a result, however I do not know whether these are good given the problems. Below you see the output. >> >> My second question is: should I standardize the spatwmat command, or use binary? I could not find in the help files what these do, in 'real' explanation. >> >> Thanks for your consideration, >> >> >> Joost Bruijsten >> >> >> >> . spatwmat, name(test7) xcoord(x) ycoord(y) band(0 10991) >> >> >> The following matrix has been created: >> >> 1. Inverse distance weights matrix test7 >> Dimension: 13x13 >> Distance band: 0< d<= 10991 >> Friction parameter: 1 >> Minimum distance: 950.2 >> 1st quartile distance: 11229.2 >> Median distance: 21674.2 >> 3rd quartile distance: 36380.2 >> Maximum distance: 70773.6 >> Largest minimum distance: 10990.63 >> Smallest maximum distance: 38792.54 >> >> >> >> . >> . >> . spatgsa aantalpersonen, weights(test7) moran >> >> >> Measures of global spatial autocorrelation >> >> >> Weights matrix >> -------------------------------------------------------------- >> Name: test7 >> Type: Distance-based (inverse distance) >> Distance band: 0.0< d<= 10991.0 >> Row-standardized: No >> -------------------------------------------------------------- >> >> Moran's I >> -------------------------------------------------------------- >> Variables | I E(I) sd(I) z p-value* >> --------------------+----------------------------------------- >> aantalpersonen | -0.189 -0.083 0.211 -0.499 0.309 >> -------------------------------------------------------------- >> *1-tail test >> >> >> _________________________________________________________________ >> Hotmail has tools for the New Busy. 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