title: Most mature sparse matrix package for R?
body: <p>There are at least two sparse matrix packages for R.  I'm looking into these because I'm working with datasets that are too big and sparse to fit in memory with a dense representation.  I want basic linear algebra routines, plus the ability to easily write C code to operate on them.  Which library is the most mature and best to use?</p>
  
  <p>So far I've found</p>
  
  <ul>
  <li><a href="http://cran.r-project.org/web/packages/Matrix" rel="noreferrer">Matrix</a> which has many reverse dependencies, implying it's the most used one.</li>
  <li><a href="http://cran.r-project.org/web/packages/SparseM/index.html" rel="noreferrer">SparseM</a> which doesn't have as many reverse deps.</li>
  <li>Various graph libraries probably have their own (implicit) versions of this; e.g. <a href="http://cran.r-project.org/web/packages/igraph/index.html" rel="noreferrer">igraph</a> and <a href="http://cran.r-project.org/web/packages/network/index.html" rel="noreferrer">network</a> (the latter is part of <a href="http://statnetproject.org/" rel="noreferrer">statnet</a>).  These are too specialized for my needs.</li>
  </ul>
  
  <p>Anyone have experience with this?</p>
  
  <p>From searching around <a href="http://rseek.org" rel="noreferrer">RSeek.org</a> a little bit, the <a href="http://cran.r-project.org/web/packages/Matrix" rel="noreferrer">Matrix</a> package seems the most commonly mentioned one.  I often think of <a href="http://cran.r-project.org/web/views/" rel="noreferrer">CRAN Task Views</a> as fairly authoritative, and the <a href="http://cran.r-project.org/web/views/Multivariate.html" rel="noreferrer">Multivariate Task View</a> mentions Matrix and SparseM.</p>