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 <
Camarda@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
>
>
>
>
>
>
>
> ----------
> This mail has been sent through the MPI for Demographic ...{{dropped:10}}
>
> ______________________________________________
> R-help@r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide
> http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>

	[[alternative HTML version deleted]]

