[R-sig-eco] mvpart alternatives and machine learning multivariate analysis

Ralf Schäfer senator at ecotoxicology.de
Sat Jun 24 18:10:27 CEST 2017


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


> Am 24.06.2017 um 18:02 schrieb Torsten Hauffe <torsten.hauffe at gmail.com>:
> 
> 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/ <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 Schäfer <senator at ecotoxicology.de <mailto:senator at ecotoxicology.de>> wrote:
> 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:
> 
> > R version 3.4.0 (2017-04-21)
> > Platform: x86_64-apple-darwin15.6.0 (64-bit)
> > Running under: macOS Sierra 10.12.5
> >
> > Matrix products: default
> > BLAS: /Library/Frameworks/R.framework/Versions/3.4/Resources/lib/libRblas.0.dylib
> > LAPACK: /Library/Frameworks/R.framework/Versions/3.4/Resources/lib/libRlapack.dylib
> >
> > locale:
> > [1] de_DE.UTF-8/de_DE.UTF-8/de_DE.UTF-8/C/de_DE.UTF-8/de_DE.UTF-8
> >
> > attached base packages:
> > [1] stats     graphics  grDevices utils     datasets  methods   base
> >
> > other attached packages:
> > [1] mvpart_1.6-2
> >
> > loaded via a namespace (and not attached):
> > [1] compiler_3.4.0
> 
> 
> 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
> 
> 
> 
> > Am 24.06.2017 um 17:47 schrieb Manuel Spínola <mspinola10 at gmail.com <mailto:mspinola10 at gmail.com>>:
> >
> > 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 Schäfer <senator at ecotoxicology.de <mailto:senator at ecotoxicology.de> <mailto:senator at ecotoxicology.de <mailto:senator at ecotoxicology.de>>>:
> > 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/ <https://cran.r-project.org/src/contrib/Archive/mvpart/> <https://cran.r-project.org/src/contrib/Archive/mvpart/ <https://cran.r-project.org/src/contrib/Archive/mvpart/>>
> >
> > Best regards
> > Ralf
> >
> >
> >> Date: Fri, 23 Jun 2017 13:59:13 -0600
> >> From: Manuel Sp?nola <mspinola10 at gmail.com <mailto:mspinola10 at gmail.com> <mailto:mspinola10 at gmail.com <mailto:mspinola10 at gmail.com>>>
> >> To: "r-sig-ecology at r-project.org <mailto:r-sig-ecology at r-project.org> <mailto:r-sig-ecology at r-project.org <mailto:r-sig-ecology at r-project.org>>" <r-sig-ecology at r-project.org <mailto:r-sig-ecology at r-project.org> <mailto:r-sig-ecology at r-project.org <mailto:r-sig-ecology at r-project.org>>>
> >> Subject: [R-sig-eco] mvpart alternatives and machine learning
> >>      multivariate    analysis
> >> Message-ID:
> >>      <CABkCotRiCwJjsh=_hsONMsh+OE52rC7L6E3Q4ssOUM=6w3DXTw at mail.gmail.com <mailto:6w3DXTw at mail.gmail.com> <mailto:CABkCotRiCwJjsh <mailto:CABkCotRiCwJjsh>=_hsONMsh+OE52rC7L6E3Q4ssOUM=6w3DXTw at mail.gmail.com <mailto:6w3DXTw at mail.gmail.com>>>
> >> Content-Type: text/plain; charset="UTF-8"
> >>
> >> Dear list members,
> >>
> >> As mvpart has been removed form the CRAN repository, Is there any r package
> >> that do similar analysis (multivariate partitioning)?
> >>
> >> Also, is there any other machine learning technique to do multivariate
> >> analysis as done in ecology to asses multiple species-environment
> >> relationships?
> >>
> >> Thank you very much in advance,
> >>
> >> Manuel
> >>
> >> --
> >> *Manuel Sp?nola, Ph.D.*
> >> Instituto Internacional en Conservaci?n y Manejo de Vida Silvestre
> >> Universidad Nacional
> >> Apartado 1350-3000
> >> Heredia
> >> COSTA RICA
> >> mspinola at una.cr <mailto:mspinola at una.cr> <mailto:mspinola at una.cr <mailto:mspinola at una.cr>> <mspinola at una.ac.cr <mailto:mspinola at una.ac.cr> <mailto:mspinola at una.ac.cr <mailto:mspinola at una.ac.cr>>>
> >> mspinola10 at gmail.com <mailto:mspinola10 at gmail.com> <mailto:mspinola10 at gmail.com <mailto:mspinola10 at gmail.com>>
> >> Tel?fono: (506) 8706 - 4662
> >> Personal website: Lobito de r?o <https://sites.google.com/site/lobitoderio/ <https://sites.google.com/site/lobitoderio/> <https://sites.google.com/site/lobitoderio/ <https://sites.google.com/site/lobitoderio/>>>
> >> Institutional website: ICOMVIS <http://www.icomvis.una.ac.cr/ <http://www.icomvis.una.ac.cr/> <http://www.icomvis.una.ac.cr/ <http://www.icomvis.una.ac.cr/>>>
> >
> >
> >
> > --
> > Manuel Spínola, Ph.D.
> > Instituto Internacional en Conservación y Manejo de Vida Silvestre
> > Universidad Nacional
> > Apartado 1350-3000
> > Heredia
> > COSTA RICA
> > mspinola at una.cr <mailto:mspinola at una.cr> <mailto:mspinola at una.ac.cr <mailto:mspinola at una.ac.cr>>
> > mspinola10 at gmail.com <mailto:mspinola10 at gmail.com> <mailto:mspinola10 at gmail.com <mailto:mspinola10 at gmail.com>>
> > Teléfono: (506) 8706 - 4662
> > Personal website: Lobito de río <https://sites.google.com/site/lobitoderio/ <https://sites.google.com/site/lobitoderio/>>
> > Institutional website: ICOMVIS <http://www.icomvis.una.ac.cr/ <http://www.icomvis.una.ac.cr/>>
> 
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