Multi response GAM
It might be possible via the VGAM package: https://cran.r-project.org/package=VGAM But I've never used this package, so not sure. It may also be possible to use a single response, by including additional explanatory terms. This is what I would do, if I could... Noting that some GAM implementations allow categorical variables and interactions. On Sat, Apr 18, 2020 at 11:00 AM Tristan Kosciuch
<tristan.kosciuch at mail.mcgill.ca> wrote:
Hello,
I am modelling the diet of Nile perch through time. I have 3 diet classes as
my response variables; fish 1, fish 2, and invertebrates.
The response variables are correlated, declines in invert consumption ~
increase in fish consumption. Any advice on how to handle this would be
appreciated. I would like to use GAMs as my time series shows fluctuations
that could only be fit by high order polynomials if I were to use a linear
model, but open to suggestions.
Thank you for your time.
P.s. I will be comparing the fit of the time series GAM with a model based
on other predictors, with a training and validation split for my data.
---
Tristan Kosciuch
Stewart Biology Building, McGill University
1205 Dr Penfield Ave, Montreal QC H3A 1B1
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