[R-sig-eco] Using multiple species data for gam

[Gavin Simpson]

I doubt VGAM's CAO will be able to handle such data, the computational
burden is just huge under that modelling framework.

The "old" way would be to just do CCA (Canonical Correspondence Analysis)
on those data, though I may get told off by David Warton for suggesting it
:-)

G

On 10 February 2015 at 03:53, Eduard Szöcs <szoecs at uni-landau.de> wrote:

> Dear Rajendra,
>
> your post reminds me on constrained additive ordination [1].
>
> [1] Yee, T. W. (2006) Constrained additive ordination. Ecology, 87,
> 203–213.
>
> All the best,
>
> Eduard Szöcs
>
> On 10/02/15 10:41, Rajendra Mohan panda wrote:
> > Dear All
> >
> > I have >1000 species with presence and absence (0 or 1) values and with
> > seven corresponding predictor variables. If I can run gam/glm for the
> data
> > using all species data simultaneously vs predictors. Data are arranged in
> > columns against their GPS locations (see below). I know it is possible to
> > do separately for each species.
> >
> > Your kind response is highly appreciated.
> >
> > Sites  Sp1  Sp2 Sp3 Alt Temp Pptn   Ft
> > 1A         0      1    1     20   30     1000 Evergreen
> >
> > With Best Regards
> > Rajendra M Panda
> > School of Water Resources
> > Indian Institute of Technology Kharagpur, India
> >
> >       [[alternative HTML version deleted]]
> >
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> >
>
> --
> Eduard Szöcs
> Quantitative Landscape Ecology
> Institute for Environmental Sciences
> University Koblenz-Landau
> Tel. +49 6341 280 31552
>
> http://www.uni-koblenz-landau.de/campus-landau/faculty7/environmental-sciences/landscape-ecology/Staff/eduardszoecs
>
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>



-- 
Gavin Simpson, PhD

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