title: Vectorize my thinking: Vector Operations in R
body: <p>So earlier I answered my own question on thinking in vectors in R. But now I have another problem which I can't 'vectorize.' I know vectors are faster and loops slower, but I can't figure out how to do this in a vector method:</p>
  
  <p>I have a data frame (which for sentimental reasons I like to call my.data) which I want to do a full marginal analysis on. I need to remove certain elements one at a time and 'value' the data frame then I need to do the iterating again by removing only the next element. Then do again... and again... The idea is to do a full marginal analysis on a subset of my data. Anyhow, I can't conceive of how to do this in a vector efficient way. </p>
  
  <p>I've shortened the looping part of the code down and it looks something like this:</p>
  
  <pre><code>for (j in my.data$item[my.data$fixed==0]) { # &lt;-- selects the items I want to loop 
                                              #     through
      my.data.it &lt;- my.data[my.data$item!= j,] # &lt;-- this kicks item j out of the list
      sum.data &lt;-aggregate(my.data.it, by=list(year), FUN=sum, na.rm=TRUE) #&lt;-- do an
                                                                           # aggregation
  
      do(a.little.dance) &amp;&amp; make(a.little.love) -&gt; get.down(tonight) # &lt;-- a little
                                                                     #  song and dance
  
      delta &lt;- (get.love)                                         # &lt;-- get some love
      delta.list&lt;-append(delta.list, delta, after=length(delta.list)) #&lt;-- put my love
                                                                      #    in a vector 
  }
  </code></pre>
  
  <p>So obviously I hacked out a bunch of stuff in the middle, just to make it less clumsy. The goal would be to remove the j loop using something more vector efficient. Any ideas?</p>