Message-ID: <CAHMizkNDqRz2PSFvCrM-Fhg6mqJ_Y6wu7Z0=yRBUhGo9Zqbhbw@mail.gmail.com>
Date: 2016-05-03T08:30:43Z
From: Juta Kawalerowicz
Subject: spatialpoints: each dot represents 100 individuals?
In-Reply-To: <9b43c157-98b9-4ad9-8215-31ef934a2097@HUB05.ad.oak.ox.ac.uk>
Thanks for all suggestions! I was thinking that in the end a plasible
approach would be to sample points, say if I have 100,000 and sample 1,000
then I can say that each point represents 100 people.
Juta
On Wed, Apr 27, 2016 at 11:13 PM, rubenfcasal <rubenfcasal at gmail.com> wrote:
> Alternatively, you might also consider data binning (implemented in
> several packages: KernSmooth, ks, sm, npsp ,...). This technique is
> commonly used in nonparametric statistics to reduce the computational
> time (see e.g. Wand, M. P. (1994), Fast Computation of Multivariate
> Kernel Estimators, Journal of Computational and Graphical Statistics, 3,
> 433-445).
>
> For instance, using the npsp package (maintained by me...), you could do
> something like this:
>
> library(npsp)
>
> bin <- binning(earthquakes[, c("lon", "lat")], nbin = c(50,50))
>
> # ?bin$binw? will contain the binning weights (aggregations) at
> locations ?coords(bin)?
>
> simage(bin)
>
> Additionally, you could estimate (nonparametrically) the spatial density:
>
> h <- h.cv(bin, ncv = 2)$h
>
> den <- np.den(bin, h = h)
>
> plot(den, log = FALSE, main = 'Estimated density')
>
> Best regards,
>
> Ruben.
>
>
> El 25/04/2016 a las 13:35, Juta Kawalerowicz escribi?:
> > Hi,
> >
> > I have a dataset with couple of million of points (individuals) and
> > would like to do some mapping (I have the coordinates of each point)
> > but given the number of observation I think it may be usuful to plot
> > dots which represent 100 individuals (of a given group). Does anyone
> > know a good way to aggregate up spatialpoints? Any suggestions would
> > be much appreciated!
> >
> > Best wishes,
> > Juta
> >
> > _______________________________________________
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> > R-sig-Geo at r-project.org
> > https://stat.ethz.ch/mailman/listinfo/r-sig-geo
> >
>
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