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

[Rajendra Mohan Panda]

I regret that the error message was due to my  erroneous data. However, I
face another error message in VGAM run i.e., object "eta" not found. Kindly
explain why this happens and possible solutions for this.

Thanks in advance

Best Regards
Rajendra M Panda
School of Water Resources
Indian Institute of Technology Kharagpur

---------- Forwarded message ----------
From: Rajendra Mohan Panda <rmp.iit.kgp at gmail.com>
Date: 2 September 2015 at 18:08
Subject: Re: [R-sig-eco] Using multiple species data for gam
To: r-sig-ecology at r-project.org


Dear All

I find it difficult to run VGAM and MARS for multi-response data. In both
the models, I get an error message "variable names are limited to 10000
bytes". Is this due to my big data structure or else ? For your kind
information, I have 1500 spp. on 434 site locations, and I want to see the
impact of environment on community structure. I have to analyse how the
Western Himalaya community behaviour differ from the Eastern Himalaya.

I have been struggling to accommodate my data for model fitting since long,
could you please give some insights on my idea and how can I tackle the
error for successful model run.

I always appreciate your valuable advise.


Best Regards
Rajendra M Panda
School of Water Resources
Indian Institute of Technology Kharagpur

On 18 February 2015 at 09:32, Rajendra Mohan panda <rmp.iit.kgp at gmail.com>
wrote:

> Dear Prof David Warton
>
> Thanks a lot for your nice introspection on my data. I appreciate your
> valuable comments. I am also trying to explore gamm or VGAM to match its
> suitability with data. Its fine. However, I am thinking to reduce my data
> structure by removing some of the species showing interspecific
> correlation. Honestly speaking I do not have thought of it. Can you please
> give more insights regarding this (interspecies correlation). I am also
> interested in studying species-environment relationship (not by CCA or RDA).
>
> Your kind comments are highly appreciated.
>
>
> With Best Regards
> Rajendra M Panda
> School of Water Resources
> Indian Institute of Technology Kharagpur, India
>
> On Wed, Feb 18, 2015 at 4:36 AM, David Warton <david.warton at unsw.edu.au>
> wrote:
>
>> Hi Rajendra and Greg,
>> A couple of quick thoughts:
>>
>> Firstly, Rajendra the method that is applicable to your data really
>> depends on the research question - what is it that you are trying to
>> achieve.  It is always hard to offer help on what analysis method is suited
>> to a question without knowing the original research objective.  The gamm
>> function for example might be useful to you if you are primarily interested
>> in predictive modelling, and also if you think that you have a common
>> nonlinear response to environmental variables with some "noise" around this
>> pattern for different spp (which can be represented as random effects).
>> You could alternatively use this function to fit a separate smoother for
>> each spp but that would be a pretty complicated model and few would have
>> sufficient data to justify that level of model complexity.  VGAM y Thomas
>> Yee offers and option in between these two.
>>
>> Secondly, something you need to worry about with this type of data is
>> interspecies correlation - for various reasons (including species
>> interaction), it is widely thought and even better often observed that
>> species are correlated in abundance (or presence/absence, whatever) even
>> after accounting for environmental predictors.  This makes the problem
>> multivariate.  If you care about making joint inferences across species and
>> you don't account for correlation between species you can get things quite
>> wrong.  The gamm function I think could handle residual correlation, but
>> not the way you specified it, and it would have a lot of trouble, unless
>> you have only a handful of species and quite decent abundance data on
>> each.  On the other hand if you are just making predictions separately for
>> each spp then you don't need to worry too much about this.
>>
>> All the best
>> David
>>
>>
>> David Warton
>> Professor and Australian Research Council Future Fellow
>> School of Mathematics and Statistics and the Evolution & Ecology Research
>> Centre
>> The University of New South Wales NSW 2052 AUSTRALIA
>> phone (61)(2) 9385-7031
>> fax (61)(2) 9385-7123
>>
>> http://www.eco-stats.unsw.edu.au/ecostats15.html
>>
>>
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