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The UK government provides a dataset on all UK postcodes under a modified UK OGL license. http://opendatacommunities.org/data/postcodes Some factors you may want to consider in your analysis: Distribution Reference: Population or Occupied Housing Units Variables: Land Use/Zoning Gross Domestic Product (GDP) per capita Government Subsidized Housing ...


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Well I can think of the following approach. I assume that you don't have access to the whole dataset of the entire postcodes. In general spatial distribution of postcodes will be similar to the population density or to the density of buildings. You can easily get most of the buildings of the UK from the OpenStreetMap. Converth them to points. Create a kernel ...


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Solution found! R.univar, despite the name, can actually calculate statistics on multiple raster at ones. My bad for not checking thoroughly. Thanks markusN for answering me..


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You were right, the r.series manual page was a bit lousy. I have hopefully improved it now. Comments certainly welcome. Concerning quantiles, if you want a single, i.e. a global map value, then check r.quantile or r.univar Example: Calculation of multiple elevation quantiles, results are printed and not stored as a new map: g.region rast=elevation -p ...


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From GWR by Roger Bivand: Geographically weighted regression (GWR) is an exploratory technique mainly intended to indicate where non-stationarity is taking place on the map, that is where locally weighted regression coefficients move away from their global values. Its basis is the concern that the fitted coefficient values of a global model, ...



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