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    <p>I don't have a bright idea, but you can get rid of the inner loop, and speed up things a bit. Notice that if a window falls fully wihtin a mylist interval, then you just have to add 100 to the corresponding <code>windows</code> element. So only the <code>st</code>-th and <code>sp</code>-th windows need special handling.</p> <pre><code> windows &lt;- numeric(100) for(i in 1:length(mylist)){ win &lt;- mylist[[i]] # for cleaner code st &lt;- floor(win[1]/100)+1 sp &lt;- floor(win[2]/100)+1 # start and stop are within the same window if (sp == st){ windows[st] &lt;- windows[st] + (win[2]%%100) - (win[1]%%100) +1 } # start and stop are in separate windows - take care of edges if (sp &gt; st){ windows[st] &lt;- windows[st] + 100 - (win[1]%%100) + 1 windows[sp] &lt;- windows[sp] + (win[2]%%100) } # windows completely inside win if (sp &gt; st+1){ windows[(st+1):(sp-1)] &lt;- windows[(st+1):(sp-1)] + 100 } } </code></pre> <p>I generated a bigger list:</p> <pre><code> cuts &lt;- sort(sample(1:10000, 70)) # random interval endpoints mylist &lt;- split(cuts, gl(35,2)) </code></pre> <p>and got 1.08 sec for 1000 replicates of this version versus 1.72 sec for 1000 replicates for the original. With real data the speed-up will depend on whether the intervals in <code>mylist</code> tend to be much longer than 100 or not.</p> <p>By the way, one could rewrite the inside loop as a separate function, and then <code>lapply</code> it over <code>mylist</code>, but that does not make it work faster.</p>
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    1. POR optimization: How can I avoid a for loop in this situation?
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