text: user1606: Given a normal protein sequence with the 20 standard amino acids, how can the 'Autocovariances', 'autocorrelations', and 'autocorrelation coefficients' of the sequence be calculated?
  What is meant by these terms in the context of a protein sequence?
  What are the appropriate algorithms and formulas?
  Is there any existing package/function to calculate these values?
  
  user920: Protein autocorrelation is similar to usual autocorrelation of time series (that is, function $r(k)$ measuring correlation between values lagged by $k$), except that instead of time dimension we slide along the backbone of amino acid chain. The "dependent variable" can be any quantifiable property of the amino acids - then the autocorrelation measures similarity in that particular property.
  See e.g. Fernandez et al., 2008, for more extensive background:
  https://www.tandfonline.com/doi/full/10.1080/08927020802301920?scroll=top&needAccess=true
  
original_text: 1606: <p>Given a normal protein sequence with the 20 standard amino acids, how can the 'Autocovariances', 'autocorrelations', and 'autocorrelation coefficients' of the sequence be calculated?</p>
  
  <p>What is meant by these terms in the context of a protein sequence?</p>
  
  <p>What are the appropriate algorithms and formulas?</p>
  
  <p>Is there any existing package/function to calculate these values?</p>
   920: <p>Protein autocorrelation is similar to usual autocorrelation of time series (that is, function <span class="math-container">$r(k)$</span> measuring correlation between values lagged by <span class="math-container">$k$</span>), except that instead of time dimension we slide along the backbone of amino acid chain. The "dependent variable" can be any quantifiable property of the amino acids - then the autocorrelation measures similarity in that particular property.</p>
  
  <p>See e.g. Fernandez et al., 2008, for more extensive background:
  <a href="https://www.tandfonline.com/doi/full/10.1080/08927020802301920?scroll=top&amp;needAccess=true" rel="nofollow noreferrer">https://www.tandfonline.com/doi/full/10.1080/08927020802301920?scroll=top&amp;needAccess=true</a></p>
  