Thank you very much Vincent,
Your answer is completely acceptable. I have used (occasionally) ASReml and
am aware of your solution. However, I would prefer staying within the R
framework (i.e. use CRAN open source packages). Similar requests have been
made in November 2011, but are still unanswered as far as I know.
Philippe
On Mon, Oct 1, 2012 at 1:28 PM, Vincent Careau wrote:
> Hi,
> I would say ASReml-R. It is free for academics using Windows. I don't know
> if someone else figured out how to do an animal model (that seems like what
> you want to do - or something very similar) with other mixed model packages
> in R. ASReml-R uses the Average Information algorithm. Perhaps the typical
> methods used for the R packages would take too long with as many random
> effects as an animal model is trying to estimate.
>
> By the way, Matt Wolak just created the "nadiv" package that you can use to
> include dominance in your animal model, given you have the pedigree links
> to
> estimate it independently from additive genetic variance.
> Good luck,
> vc
>
> Vincent Careau
> NSERC Postdoctoral fellow
> Department of Biology
> University of California
> Riverside, CA, 92521
> http://faculty.ucr.edu/~vcareau/
>
>
> -----Original Message-----
> From: r-sig-mixed-models-bounces@r-project.org
> [mailto:r-sig-mixed-models-bounces@r-project.org] On Behalf Of philippe
> fullsack
> Sent: Monday, October 01, 2012 5:58 AM
> To: r-sig-mixed-models@r-project.org
> Subject: [R-sig-ME] user-defined covariance matrix for linear mixed models
>
> I am looking for an R package or function that would estimate the
> variance-covariance matrix of a linear mixed model.
> I have used pedigreemm and lme4 for simple examples but I would like to
> know how to provide my own covariance structure.
> E.g. G, the variance-covariance matrix of a lmm model will typically be the
> tensor product of a typically small matrix g (e.g. a 2 x2 matrix of 3
> variance-covariance parameters to estimate : sigxx,sigxy,sigyy) with of a
> known matrix A. I wish to read matrix A from a file, and ask the R function
> to estimate g. I am not interested only in the case of diagonal g matrices.
>
> Is anybody aware of an interface e.g. to lme4, that would allow users to
> specify and fit their models in such, flexible, way?
> Please specify in your answer the input format for A (i.e sparse CSR,
> dense, trios, or any) - (g is in dense format).
>
> Note that a package like Jarrod Hadfield's MCMCglmm allows such flexible
> definitions. However, I am looking for a non MCMC estimator (e.g. REML).
>
> P.Fullsack
> Dalhousie University
>
> [[alternative HTML version deleted]]
>
> _______________________________________________
> R-sig-mixed-models@r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models
>
>
[[alternative HTML version deleted]]