[R-sig-ME] Error in .local(object, n, verbose, ...) : Update not yet written

[Ben Bolker]

joana martelo <jmmartelo at ...> writes:

> 
> Many thanks Ben! 
> 
> What I would like is to get the parameter estimates and confidence intervals
> based both on the fixed and random effects, and not just on the fixed
> effects. Is parametric bootstrapping the only alternative?
> 
> Thanks again!
> 
> Joana

  Yes, unless you use Bayesian methods (MCMCglmm etc.), or
glmmADMB with MCMC sampling ('pseudo-Bayesian'), or you
manage to get your GLMMs working with profiling in the
development version of lme4 (experimental!)

  (As always I would be happy for enlightenment from other
list readers if they have any ideas!  Is there a straightforward
way to do this in SAS or AS-REML?)

[snip]
> 
>   mcmcsamp has never worked for GLMMs and at this point probably never will,
> because writing a reliable post-hoc MCMC sampler (i.e., one that doesn't get
> stuck at low parameter valuables or have other undesirable behaviour) has
> turned out to be really, really hard.
> 
>   If you really want the posterior distribution of the parameters, it should
> be pretty easy to fit your model using MCMCglmm.  If you want confidence
> intervals it's unfortunately harder than it should be, but you might try
> parametric bootstrapping ... (the pbkrtest package has parametric
> bootstrapping, but it is designed for parameter testing via model comparison
> rather than for finding posterior/sampling distributions of parameters).
> 
>   Ben Bolker