UNSOLVED: Re: lme4 or other open source mixed model package code equivalent to asreml-R
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) ?