[R-sig-ME] UNSOLVED: Re: lme4 or other open source mixed model package code equivalent to asreml-R

[Ben Bolker]

David Duffy <David.Duffy at ...> writes:

> 
> On Thu, 17 Nov 2011, John Clark wrote:
> 
> > Thank you for mails. The questions is still open to suggestion. I have
> > improved the description of the model. It is easier to do in stackoverflow
> > to paste figures etc. Please find the improved question.
> >
> >
http://stackoverflow.com/questions/7961864/lme4-or-other-open-source-r-package-code-equivalent-to-asreml-r
> >
> >
> > On Wed, Nov 2, 2011 at 1:25 PM, Kevin Wright <kw.stat at ...> wrote:
> >
> >> I have searched for many years for examples of fitting AR1xAR1 type models
> >> with open-source software other than ASREML.  There are no such examples.
> >> Only ASREML (and SAS PROC MIXED) can fit these models.
> >
> 
> You might look at the regress and spatialCovariance packages of David 
> Clifford.  The former allows fitting of (Gaussian) mixed models where you 
> can specify the structure of the covariance matrix very flexibly (for 
> example, I have used it for pedigree data).  The spatialCovariance package 
> uses regress to provide more elaborate models than AR1xAR1, but may be 
> applicable.  You may have to correspond with the author about applying it 
> to your exact problem.

  Hmm.  I took a quick look; it is nice to see another implementation
of mixed effects models (you can never have too many, especially when
they're open and can build on each other ...) -- BUT -- it's not 
immediately obvious to me (maybe this is the "correspond with the author"
part?) how to construct this problem so that the variance structure
corresponds to a sum of specified Gaussian values.  In particular, would
we have to use an outer loop to profile over different values of the
scale parameter (or run a 1-dimensional minimum-finder for the
negative log-likelihood) ?