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Dear INLA experts,
I am considering a complicated non-linear model, The model structure is:
η1=β1⋅x
η2=β2⋅x
η3=β3⋅x
y1=exp(η1)
y2=exp(η2)
y3=exp(η3)
Y=y1+y2+y3
P1=y1/Y; P2=y2/Y; P3=y3/Y
My data include Y, P1, P2, P3, and x. Is it possible to fit this model in INLA Since Y and P are defined using exp(linear predictor), it complicates the modeling process. Any guidance is appreciated!
Thanks,
Ruby
Håvard Rue
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Dec 13, 2024, 1:53:31 AM12/13/24
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to Ruby Ji, R-inla discussion group
short answer: no
maybe INLABRU can do this ?
this is similar to multinomial data, which is rewritten into poisson (see
vignette), but you observe the sum, not the the individuals. well, you need an
individual random effect pr 'vector' of observations, but still.
its not difficult to do this per se, just that INLA is not implemented to do so