Dear all,
I have a spatial point data (lat-long) with 1000 points representing
pooling stations (all within a given city). Each point has two variables
attached to it: number of population registered to the pooling station and
city region to which the pooling stations belong.
What I am trying to do is to sample random electoral districts that cluster
those points. Thus, in each iteration of the sampling I would end up having
somewhat different districts in whithin the city.
Just to better specify what I mean by "districts", I am trying to sample
contiguous clusters with the spatial points, based on three criteria: 1)
proximity; 2) all clusters should end up having similar populations size
(cluster population meaning the summed population registered in each of its
assigned points) and 3) different points that belong to the same city
region should preferably stay in the same clusters.
I've been trying with SKATER function and other non-implemented approaches,
but still no luck. Any suggestions on how to implement that? Any packages,
code sampling or reading suggestions will be very much appreciated.
Thanks for your attention!
Fabricio
[[alternative HTML version deleted]]
_______________________________________________
R-sig-Geo mailing list
[email protected]
https://stat.ethz.ch/mailman/listinfo/r-sig-geo
