Thank you very much David,
Are you suggesting to use the regress function with Vformula:
     G = sxx. [ A  0 ]      + sxy  [ 0 A ]    + syy [ 0 0 ]
                   [ 0  0 ]                 [ A 0 ]             [ 0 A ]
( a linear combination of known symmetric matrices)

assuming a blocking of random effects : G = cov([u1,u2],[u1,u2]) ?



On Mon, Oct 1, 2012 at 9:14 PM, David Duffy <David.Duffy@qimr.edu.au> wrote:

> On Mon, 1 Oct 2012, philippe fullsack wrote:
>
>  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
>>
>>
>  library(help=regress)
>
>
> Version:              1.3-8
> Date:                 2012-03-19
> Title:                Gaussian linear models with linear covariance
>                       structure
> Author:               David Clifford and Peter McCullagh. Additional
>                       contributions by HJ Auinger.
> Maintainer:           David Clifford <david.clifford@csiro.au>
> Description:          Functions to fit Gaussian linear model by
>                       maximising the residual log likelihood where the
>                       covariance structure can be written as a linear
>                       combination of known matrices.  Can be used for
>                       multivariate models and random effects models.
>                       Easy straight forward manner to specify random
>                       effects models, including random interactions.
>
>
>
> --
> | David Duffy (MBBS PhD)                                         ,-_|\
> | email: davidD@qimr.edu.au  ph: INT+61+7+3362-0217 fax: -0101  /     *
> | Epidemiology Unit, Queensland Institute of Medical Research   \_,-._/
> | 300 Herston Rd, Brisbane, Queensland 4029, Australia  GPG 4D0B994A v
>

	[[alternative HTML version deleted]]

