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: marchy...@hotmail.com
> To: tintin...@hotmail.com; r-help@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).
>
>
>
> ----------------------------------------
> From: tintin...@hotmail.com
> To: r-help@r-project.org
> Date: Thu, 17 Mar 2011 17:38:14 +0100
> Subject: [R] Spatial cluster analysis of continous outcome variable
>
>
>
> 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 don´t know if it´s 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 don´t have many points.
> Thanks in advance
>
>
>
>
>
> J Toledo
> [[alternative HTML version deleted]]
>
>
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