title: What are `trait:units` and `variance.function(trait):units` in `MCMCglmm`?
body: <p>I am trying to perform a <code>MCMCglmm</code> of the kind</p>
  
  <pre><code>df=data.frame(y=rep(c(0:2),each=12),x=rnorm(3*12))
  MCMCglmm(data=df,fixed=y~x, family="categorical")
  </code></pre>
  
  <p>and I get the error message</p>
  
  <pre><code>For error structures involving catgeorical data with more than 2 categories pleasue use trait:units or variance.function(trait):units.
  </code></pre>
  
  <p>I had a quick look at <a href="ftp://cran.r-project.org/pub/R/web/packages/MCMCglmm/vignettes/CourseNotes.pdf" rel="nofollow">Jarrod Hadfield's course notes</a> but did not find much specification about this notation and its meaning.</p>
  
  <p>What does the notations <code>trait:units</code> and <code>variance.function(trait):units</code> mean? How would one typically use them?</p>
  
  <p>I welcome you to for example consider the command</p>
  
  <pre><code> m &lt;- MCMCglmm(LetVerb ~ -1 + trait + trait:(Channel + CrSem + MS),
  random = ~us(trait):Vinf, rcov = ~ us(trait):units, data = letting,
  family = "categorical", prior = priors, verbose = TRUE, burnin =
  10000, nitt = 60000, thin = 50)
  </code></pre>
  
  <p>from the third page of this <a href="http://www.natalialevshina.com/Documents/MCMCglmm_Tutorial.pdf" rel="nofollow">tutorial</a></p>