text: user191: When using branch-site model in Godon, model optimization results include the following parameters: p01sum and p0prop. What are those and how do they relate to p0 and p1 in the branch-site model?
  
  user191: Disclaimer: I'm the author of godon. The question above comes from the real communication with a software user.
  In the godon implementation of the branch-site model I performed the following reparametrization:
  $p_{01sum} = p_0 + p_1$
  $p_{0prop} = \frac{p_0}{p_0 + p_1}$.
  This has the following advantages:
  
  Both parameters have a well defined range $(0, 1)$.
  There is less dependency between the two. E.g., $p_2=1-p_0-p_1$ (proportion of sites under positivie selection) does not depend on $p_{0prop}$.
  Both properties are very helpful for both likelihood maximization and MCMC.
  
  In case you are interested in $p_0$ and $p_1$ there is a straightforward way to go back to the original parameters:
  $p_0=p_{0prop}*p_{01sum}$
  $p_1=p_{01sum}-p_0$.
  P.S. I also added this information to the tutorial.
  
original_text: 191: <p>When using branch-site model in <a href="https://bitbucket.org/Davydov/godon/" rel="nofollow noreferrer">Godon</a>, model optimization results include the following parameters: <code>p01sum</code> and <code>p0prop</code>. What are those and how do they relate to <code>p0</code> and <code>p1</code> in the branch-site model?</p>
   191: <p><strong>Disclaimer</strong>: I'm the author of godon. The question above comes from the real communication with a software user.</p>
  
  <p>In the godon implementation of the branch-site model I performed the following reparametrization:</p>
  
  <p><span class="math-container">$p_{01sum} = p_0 + p_1$</span></p>
  
  <p><span class="math-container">$p_{0prop} = \frac{p_0}{p_0 + p_1}$</span>.</p>
  
  <p>This has the following advantages:</p>
  
  <ul>
  <li>Both parameters have a well defined range <span class="math-container">$(0, 1)$</span>.</li>
  <li>There is less dependency between the two. E.g., <span class="math-container">$p_2=1-p_0-p_1$</span> (proportion of sites under positivie selection) does not depend on <span class="math-container">$p_{0prop}$</span>.</li>
  <li>Both properties are very helpful for both likelihood maximization and MCMC.</li>
  </ul>
  
  <p>In case you are interested in <span class="math-container">$p_0$</span> and <span class="math-container">$p_1$</span> there is a straightforward way to go back to the original parameters:</p>
  
  <p><span class="math-container">$p_0=p_{0prop}*p_{01sum}$</span></p>
  
  <p><span class="math-container">$p_1=p_{01sum}-p_0$</span>.</p>
  
  <p>P.S. I also added this information to the <a href="https://github.com/idavydov/godon-tutorial" rel="nofollow noreferrer">tutorial</a>.</p>
  