title: About negative binomial regression in large data
body: <p>I have a data about 19 columns and more than 10 million rows. Now I want to run negative binomial regression. </p>
  
  <p>Since the memory is the bottleneck, I planed to use <code>ff</code> package to deal with the issue. But it turned out that the function <code>glm.nb</code> in <code>MASS</code> package cannot be used in this case. And there's a <code>ffbase</code> package, which have some enhanced functions, but without glm.nb.</p>
  
  <p>Also<code>bigmemory</code> and <code>biganalytics</code>packages have such problems.</p>
  
  <p>I don't know whether my understanding is correct. Or there's indeed a feasible way to incorporate <code>ff</code> and <code>MASS</code>. So how to proceed in the next?</p>
  
  <p>PS, I use windows...which seems to be a curse dealing with such large data..</p>
  
  <p>Any link, comments, or tips are appreciated! </p>