[R-sig-Geo] Geographically weighted regression on categorical variable

[Dominik Schneider]

Sorry I don't know the answer but you can search here:
http://grokbase.com/g/r/r-sig-geo

On Mon, Jul 18, 2016 at 12:13 PM, Guy Bayegnak <Guy.Bayegnak at gov.ab.ca>
wrote:

>
> Hi All,
>
> I am trying to perform geographically weighted regression on categorical
> variables.  The majority of answers I found on the web suggest that this is
> not doable or not recommended.  I found only one post from Roger Bivan (
> https://stat.ethz.ch/pipermail/r-help/2007-September/141586.html ) that
> indicated that it was possible, and that the R-sig-geo list is more focused
> on this kind of question. I have therefore registered, but I am not sure if
> the mailing list is "searchable".
>
> I have point data collected over a geographical area A.  My data are
> groundwater quality type. And I have 3 types. When I plot it of a map it
> looks like 2 of the types are clustered and occur next to each other.  My
> suspicion is that these two clustered type may be influenced by their
> proximity to the some potential sources.  I used the spatstats package to
> explore the data,  using L-cross function.  The result of the analysis show
> that the 3 types appear to be influenced by the source, although the two
> groundwater that are clustered appear to deviate much more from the
> theoretical L-cross.  Now I am trying to explore the relationship between
> the water types and the potential source using geographically weighted
> regression on categorical variables.  Most of the material a read deals
> with continuous variables, and tend to focus on areal (polygons) features
> rather than point features.
>
> Is there any way to perform geographically weighted regression on points
> categorical variables using R?
>
> Thanks,
> GAB
>
>
>
>
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