title: Bootstrap a large data set
body: <p>I would like to bootstrap a large data set which contains multiple column and row variables.  The following is a simplified re-creation of my data set:</p>
  
  <pre><code>charDataDiff &lt;- data.frame(c('A','B','C'), matrix(1:72, nrow=9))
  colnames(charDataDiff) &lt;- c("patchId","s380","s390","s400","s410","s420","s430","s440","s450")
  </code></pre>
  
  <p>Separate the data using the <code>patchId</code> as the criteria. This creates three lists: one for each Variable</p>
  
  <pre><code>idColor &lt;-  c("A", "B", "C")
  (patchSpectrum &lt;- lapply(idColor, function(idColor) charDataDiff[charDataDiff$patchId==idColor,]))
  </code></pre>
  
  <p>Created the function <code>sampleBoot</code> to sample the <code>patchSpectrum</code> </p>
  
  <pre><code>sampleBoot &lt;-  function(nbootstrap=2, patch=3){
      return(lapply(1:nbootstrap, function(i)
               {patchSpectrum[[patch]][sample(1:nrow(patchSpectrum[[patch]]),replace=TRUE),]}))}
  </code></pre>
  
  <p>Example:</p>
  
  <pre><code>sampleBoot(5,3)
  </code></pre>
  
  <p>Here is where I am stuck: </p>
  
  <ol>
  <li>I need to sample each <code>patchId</code> list along with each column variable (which the above "sampleBoot" easily accomplish), </li>
  <li>Take the median of each <code>patchId</code> sampling list iteration, and </li>
  <li>Create a new population of the medians to calculate parametric parameters. I can do it manually but that would be silly.</li>
  </ol>