title: `TruncNorm: lower bound is greater than upper bound` Error in MNP package
body: <p>I'm using the <code>MNP</code> package to fit Bayesian multinomial probit models to categorical data. I frequently get this error: <code>TruncNorm: lower bound is greater than upper bound</code>. How can I resolve this problem?</p>
  
  <p>My sense is that this might be a convergence issue, so I've tried many different approaches on this front:</p>
  
  <ul>
  <li>narrower priors / changing priors</li>
  <li>scaling predictors, dropping highly correlated predictors</li>
  <li>start with one predictor then build up to more</li>
  </ul>
  
  <p>But none of these have worked. What I have noticed is that when <code>n.draws</code> is set to a smaller number this Error comes up less frequently. Here's an example using the Iris dataset:</p>
  
  <pre><code>library(MNP)
  data("iris")
  
  
  iris$Species = as_factor(as.character(iris$Species))
  
  
  res = mnp(Species ~ Sepal.Length, 
            data = iris,
            n.draws = 10000, verbose = TRUE)
  summary(res)
  </code></pre>
  
  <p>The model returns the <code>TruncNorm</code> error at N = 10,000, but will finish at smaller sizes of N.</p>