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mvpart alternatives and machine learning multivariate analysis

7 messages · Ralf Schäfer, Torsten Hauffe, Manuel Spínola

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Dear Manuel

despite it has been removed, it should still work.
At least I used it last year - just install the version from the archive manually:
https://cran.r-project.org/src/contrib/Archive/mvpart/

Best regards
Ralf

  
  
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Thank you Ralf,

But I guess is not going to be newer versions and could be incompatible
with newer version of R, so at some moment there will be no accessibility
to the package.

Manuel

2017-06-24 5:25 GMT-06:00 Ralf Sch?fer <senator at ecotoxicology.de>:

  
    
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Manuel,

I just checked, it is currently still compatible. So you can download from the archive and install from source - at least on Linux and OS X, nut sure about Windows.
See Session information below:
However, there are certainly other packages that can partition multivariate ecological data, though I am not aware of other packages for use with multivariate regression trees.

Regards
Ralf

  
  
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As far as I remember, on Windows you will need to download and install the
Rtools first (https://cran.r-project.org/bin/windows/Rtools/) because some
parts of mvpart need to be compiled.

You can analyse multiple species-environment relationships with the mvabund
package. This is not fancy machine-learning but solid likelihood statistic.

HTH,
Torsten
On 24 June 2017 at 11:57, Ralf Sch?fer <senator at ecotoxicology.de> wrote:

            

  
  
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Indeed! To expand on this: if you need a tutorial for mvabund, we once analysed some categorical multivariate data and provided a tutorial:
http://dx.doi.org/10.1007/s10646-015-1421-0
Paper and tutorial are freely available on researchgate

There are also many other methods, but to point you to some, it would be good if you were more specific than ?community- environment relationships?.

Best regards
Ralf

  
  
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Thank you very much Torsten.

Manuel

2017-06-24 10:02 GMT-06:00 Torsten Hauffe <torsten.hauffe at gmail.com>:

  
    
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Thank you very much Ralf.

I am looking for alternatives to the classic CCA community analysis, and I
was thinking into machine learning techniques.

Manuel

2017-06-24 10:10 GMT-06:00 Ralf Sch?fer <senator at ecotoxicology.de>: