title: Memory efficient cluster bootstrap
body: <p>I have a very large dataset (10m observations but reduced to 14 essential variables), and am following the following thread: <a href="https://stackoverflow.com/questions/66886282/cluster-bootstrapped-standard-errors-in-r-for-plm-functions/71064115#71064115">Cluster bootstrapped standard errors in R for plm functions</a></p>
  <p>My codes after loading libraries are:</p>
  <pre><code>fe_pois &lt;- fepois(totalcountdeals ~ logdist + inst_dist_std + whited_wu_std:findev_std | iso_o_code + sic2, vcov=~pair, data = cbma, nthreads = 2)
  
  boot_feols &lt;- boottest(fe_pois, clustid = &quot;pair&quot;, param = &quot;logdist&quot;, B = 199, nthreads = 2)
  
  </code></pre>
  <p>However, this fails with large enough memory.  Any other solutions.  I need to bootstrap standard errors because one of my regressors is an estimate.</p>
  <p>I have also tried filtering the data, and run the above on a sub-sample, just for a try.  New error there is;</p>
  <pre><code>Error in if (!is.numeric(lower) || !is.numeric(upper) || lower &gt;= upper) stop(&quot;lower &lt; upper  is not fulfilled&quot;) : 
    missing value where TRUE/FALSE needed
  </code></pre>