[R-sig-ME] covariance problems in MCMCglmm. genetic effects and multiple membership

[Szymek Drobniak]

Hi Unfortunately this is not possible as far as Know but please someone
correct me if I'm wrong - MCMCglmm cannot use design matrices of necessary
form for random effects. you'll have to use asreml - or asreml-r which has
syntax similar to MCMCGLMM.

Cheers
Szymek
W dniu pon., 10 sie 2015 o 19:15 Alexandre Martin <
alexandre.m.martin at gmail.com> napisał(a):

> Dear Szymek,
>
> Thank you again for your contribution with your last answer.
>
> I am wondering now how to write the model to estimate the covariance
> between the “mm(…)” and the “animal” random parts.
>
> Jarrod wrote in this thread (https://stat.ethz.ch/pipermail/r-sig-mixed-models/2011q4/017034.html) about maternal genetic effects : “*it is not yet possible to fit the covariance between maternal genetic and direct genetic effects*“
>
> Since my model is similar to that described in the thread, is it still
> impossible to fit a model to assess the covariance between direct and
> indirect genetic effects in a way similar to that in ASReml as follow?
>
>
>
> For y =Xb + Z1animal + Z2maternal + e
>
> Analysis of some kind
>
> anim !P                       # The variable ‘anim’ is related to a
> pedigree fil
>
> dam !P                        # The variable ‘dam’ is related to a
> pedigree file
>
> dage 10 !A
>
> rt 6
>
> wwt
>
> grp 322 !A
>
> example.ped
>
> example.dat
>
> wwt ~ mu rt dage !r anim dam !f grp
>
> 0 0 1
>
> anim 2
>
> 2 0 US !GP
>
> .2 0 .15
>
> anim o AINV
>
>
>
>
>
> Best
>
>
>
> Alexandre
>
>
>
>
>
> *De :* Szymek Drobniak [mailto:szymek.drobniak at uj.edu.pl]
> *Envoyé :* 14 mai 2015 17:39
> *À :* r-sig-mixed-models at r-project.org
> *Cc :* alexandre.m.martin at gmail.com
> *Objet :* Re: genetic effects and multiple membership in MCMCglmm
> (Alexandre Martin)
>
>
>
> Hello Alexandre,
>
>
>
> using ped assigns a given correlation structure only to the "animal"
> random effect. You have to create an inverse of A matrix:
>
>
>
> my_inverse <- inverseA(ped)$Ainv
>
>
>
> and assign it in MCMCglmm to specific random effects:
>
>
>
> MCMCglmm(Y~1,
> random=~animal+mm(m1+m2+m3),
>
> ginverse=list(animal=my_inverse, m1=my_inverse,
> m2=my_inverse,m3=my_inverse), data=dat, pr=T).
>
>
>
> Cheers
>
> Szymek
>

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