Re: [R] Spatial cluster analysis of continous outcome variable

From: Jon Toledo <tintin_jb_at_hotmail.com>
Date: Thu, 17 Mar 2011 21:11:36 +0100

I attach the data (csv format). There are the 3 coordinates, (but as there are not so many points I wanted two do 3 analysis in each of them collapsing one variable).There are two variables to study I have posted the data as a ratio between both states and as a percentage state between both states. The data are from different samples (and each sample has 3 or 6 measures).Thanks again.

> From: marchywka_at_hotmail.com
> To: tintin_jb_at_hotmail.com; r-help_at_r-project.org
> Subject: RE: [R] Spatial cluster analysis of continous outcome variable
> Date: Thu, 17 Mar 2011 15:20:09 -0400
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> Did you post your data or hypothetical data?
> Usually that helps make your problem more clear and more interesting
> ( likely to get a useful response to your post).
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> From: tintin_jb_at_hotmail.com
> To: r-help_at_r-project.org
> Date: Thu, 17 Mar 2011 17:38:14 +0100
> Subject: [R] Spatial cluster analysis of continous outcome variable
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> Dear R Users, R Core
> Team,
> I have a two dimensional space where I measure a numerical value in two situations at different points. I have measured the change and I would like to test if there are areas in this 2D-space where there is a different amount of change (no change, increase, decrease). I donīt know if itīs better to analyse the data just with the coordinates or if its better to group them in "pixels" (and obtain the mean value for each pixel) and then run the cluster analysis. I would like to know if there is a package/function that allows me to do these calculations.I would also like to know if it could be done in a 3D space (I have collapsed the data to 2D because I donīt have many points.
> Thanks in advance
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> J Toledo
> [[alternative HTML version deleted]]
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