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

Alexandre Martin alexandre.m.martin at gmail.com
Mon Aug 10 19:15:34 CEST 2015

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

dam !P                        # The variable ‘dam’ is related to a pedigree

dage 10 !A

rt 6 


grp 322 !A



wwt ~ mu rt dage !r anim dam !f grp 

0 0 1 

anim 2 

2 0 US !GP

.2 0 .15 

anim o AINV








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


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:



ginverse=list(animal=my_inverse, m1=my_inverse,
m2=my_inverse,m3=my_inverse), data=dat, pr=T).




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