QGglmm multivariate with fixed effects

Hi Walid,

QGparams yields the point estimates corresponding to the point estimates it was given as input. But if you work with MCMCglmm, you might want to use to obtain the whole posterior distribution of the parameters on the observed data scale (see section 5.3 of the vignette "How To"), then take the point estimate you want to use (mode, mean, median, your choice). If your binomial model uses a logit link, it might be a bit slow, as there is no close formula for this model...

Running QGmvparams accounting for fixed effects is similar to the monovariate case, but you need to pass a matrix to "predict" rather than a vector. Quoting the help page of QGmvparams:
predict: Optional matrix of predicted values on the latent scale (each
          trait in each column). The latent predicted values must be
          computed while only accounting for the fixed effects
          (marginal to the random effects). (numeric)

I'd be happy to hear any feedback on how to make the package easier to use and the "How To" easier to understand (maybe outside of the mailing list). I have been thinking about a "wrapper" function to make the process of integrating over the posterior distribution easier but I haven't had the time to implement it.

Cheers,
Pierre

Le jeudi 1 mars 2018, 17:04:58 CET Walid Mawass a ?crit :

Hello everyone,

I am working with the QGglmm package by Pierre de Villemereuil to 
calculate heritability and additive variance on the observable scale 
since my response variable is binomial and I am using MCMCglmm. I read 
his 'How to' pdf but it does not precisely say if the output represents 
the posterior mode or the mean for each parameter. Is it possible to 
compute the mode of the additive genetic variance and heritability 
instead of the mean if that is the case.

In addition, in his tutorial, he explains how to calculate the 
parameters if there are fixed effects in the model by using predict 
instead of calculating the mean of the trait. However that is only in 
the case of a univariate model, I was not successful in applying it for 
a multivariate model with fixed effects. I would appreciate it if I 
could get some help on how to proceed in this case.

Thank you

-- 
Walid Mawass

Ph.D. candidate in Cellular and Molecular Biology

Population Genetics Laboratory

University of Qu?bec at Trois-Rivi?res
3351, boul. des Forges, C.P. 500
Trois-Rivi?res (Qu?bec) G9A 5H7
Telephone: 819-376-5011 poste 3384

_______________________________________________
R-sig-mixed-models at r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models