Hi:
You could look into the gamm4 package. Its description is:
Fit generalized additive mixed models via a version of mgcv's gamm function,
using lme4 for estimation via Fabian Scheipl's trick.
HTH,
Dennis
On Wed, Sep 29, 2010 at 7:28 AM, Camarda, Carlo Giovanni <
cama...@demogr.mpg.de> wrote:
> Dear R-users,
>
> Is there any R-function for fitting generalized additive mixed
> models for ordinal data? Do they actually make some sense? I can fit a
> generalized linear mixed model for ordinal data using the function
> clmm(ordinal) and I'm able to cope with generalized additive model for
> ordinal data within the package VGAM.
> But I would like to fit something like:
>
> g(\gamma_{ij}) = \theta_{j} + x_{i1} \beta_1 + f(x_{2i}) + u_{i},
>
> where \gamma_{ij} denote the cumulative probability that the i-th
> observation falls in the j-th category or below.
>
> Sorry for the rather out-of-R question,
> Carlo Giovanni Camarda
>
>
>
>
>
>
>
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