title: How to properly code a scaled inverse Wishart prior for a MCMCglmm model?
body: <p>I am running a multivariate model (4 response variables) with two random effects using <code>MCMCglmm()</code>. I am currently using a inverse Wishart prior.</p>
  <pre><code>###current set up for prior
  prior.miw&lt;-list(R=list(V=diag(4), nu=0.002), 
                  G=list(G1=list(V=diag(4), 
                  nu=0.002,   
                  alpha.mu=c(0,0,0,0), 
                  alpha.V=diag(4)*1000),
                  G2=list(V=diag(4), #need to repeat to deal with second random effect
                  nu=0.002,   
                  alpha.mu=c(0,0,0,0), 
                  alpha.V=diag(4)*1000)))
  </code></pre>
  <p>Based on my model, it appears I should really run a scaled inverse Wishart prior (see <a href="https://onlinelibrary.wiley.com/doi/full/10.1111/oik.05985" rel="nofollow noreferrer">page 14 of Lemoine 2019</a>).</p>
  <p><a href="https://i.stack.imgur.com/RrjIN.png" rel="nofollow noreferrer"><img src="https://i.stack.imgur.com/RrjIN.png" alt="enter image description here" /></a></p>
  <p>My question: how do I make this into a prior that is suitable for my <code>MCMCglmm()</code> model?</p>
  <p><em>Additionally, if this is NOT the sort of prior I should be running, please feel free to weigh in.</em></p>