[R-sig-ME] Prior for a bivariate model
M.Fairbrother at bristol.ac.uk
Tue Feb 21 12:06:22 CET 2017
I can't answer your question, but it sounds likely that someone on the list
will be able to. However, you'll increase the chances if you can send a
snippet of your R code thus far...
What call to MCMCglmm and what specification of your prior are you using
for a univariate model for each outcome separately, for example? If you can
show people something of what you've been able to do so far, you'll likely
get a response about how to go further.
> Date: Mon, 20 Feb 2017 18:41:14 +0100
> From: Gr?gory DANIEL <daniel.gregory3 at gmail.com>
> To: r-sig-mixed-models at r-project.org
> Subject: [R-sig-ME] Prior for a bivariate model
> Message-ID: <8960d3bb-9c0c-50e4-38ed-e7763469d76b at gmail.com>
> Content-Type: text/plain; charset=utf-8; format=flowed
> Dear list members,
> I am working with MCMCglmm package on a bivariate model to estimate the
> genetic covariance between my two traits that are my response variables.
> One is binary and the other is gaussian. I have about 700 individuals,
> one measure per trait for each individual.
> The model is simple : sex as fixed effect, and animal as random effect.
> But I have been struggling for several weeks to find a proper prior for
> which the model converge concerning the "animal" variance of my binary
> variable, and to do not have a big auto-correlation between iterations
> for the same variance.
> Concerning the residual variance, I have no problem, only with the prior
> for the additive genetic variance of my binary response variable. I
> think we cannot specify two priors for a same variable...
> I hope I was clear enough... Does anyone could help me to find a
> solution please ?
> Thanks a lot,
> Gr?gory DANIEL - Ph.D. in evolutionary ecology
> mail : daniel.gregory3 at gmail.com
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